fbpx

You know that Google Search on some browsers can now highlight text and even scroll down to the portion of the page with the text from the search results page to your web page. Well, now it seems to also work not just in web searches featured snippets but also in Google Image search.

Glenn Gabe noticed the #:~:text= urls showing up URL pattern in some of his Search Console reporting:

Glenn Gabe

Isn't this interesting... A client pinged me about seeing this in their reporting. Google must be testing ScrollToText functionality in *Google Images*. I'm seeing #:~:text= urls showing up in the reporting as of 8/4 (across sites). I don't see this yet while testing:

I then asked him for the query and it was [BOM]. It worked for me, it did not work for him, in terms of being able to click on the image result and see it jump to his page, scroll down and highlight the text.

 

Here is a screen shot of the image search results page (click to enlarge):

t-google-image-search-adds-highlight-web-page-text-feature2-1597263611.jpg

Here is a screen shot showing his page highlighting the text after the scroll down (click to enlarge):

t-google-image-search-adds-highlight-web-page-text-feature-1597263580.jpg

Weird that this works on Google Images when it should seem to only work on Google Web Search, with featured snippets. Just seems weird.

Forum discussion at Twitter.

 

[Source: This article was published in seroundtable.com By Barry Schwartz - Uploaded by the Association Member: Jennifer Levin] 

Categorized in Search Engine

Learn how to find the images you're after, more quickly and efficiently, using these advanced search capabilities in Google Images.

Searching for images on Google is a simple process.

Many of us can quickly find a picture of something we are searching for by performing a basic Google image search.

Google populates the results, sometimes with ads in the first row, with rows and rows of images and then links back to their respective websites.

This is the standard image search functionality that most of us are used to seeing when we’re looking for a photo on Google.

 

It is an extremely common search result format, that clearly layouts and categorizes various types of image results.

food-processor-1-5eb9bc4527760.png

However, many of us often forget or underutilize Google’s advanced image search feature, which can help us all perform more refined image searches.

Below are a few methods to use advanced image search on Google to find images that you’re after, more quickly and efficiently.

Advanced Search Filters

By navigating to images.google.com, you can start to perform your standard image search.

The basic search bar appears for you to enter your query.

However, many do not know that by clicking “tools”, you can then see a few different advanced filters to help specify what you are looking for even further.

google-image-search-for-dogs-.jpg

You can filter image results in the following ways:

Image Size

Here you can choose from large, medium, small, or an icon.

This can help to quickly locate an image based on the specific size you are after.

Whether it be a larger “hero” image or a smaller thumbnail, this feature can make it a speedier process to specify sizes.

Image Color

You have the option of black and white, transparent, or a specific color such as blue, red, yellow, etc.

This can help to easily narrow down an image search to pick up on any certain tones or colors you’re after.

Say you are writing a blog post on beach vacations, and want some images with light blue water, you can quickly find those using this filter.

Image Usage Rights

Labeled for reuse with modification, labeled for reuse, labeled for noncommercial reuse with modification, labeled for non-commercial reuse.

This is helpful in order to easily identify what photos are up for reuse and which ones are not.

Image Type

Options include clip art, line drawing, and GIF.

This can help to easily locate images based on animation or illustration type.

Time

Options include the past 24 hours, past week, past month, past year.

This can help to pin down more recent photos that may be more relevant, dependent on the topic you are after.

Google Advanced Image Search

Now, by navigating to Google’s Advanced Image Search, you will find that this tool uses all of the filters listed above, and then some.

If you still cannot find a specific image that you are after with the basic filters, this is a great tool to try.

google-advanced-image-search-5eba883ed387c.png

This Exact Word or Phrase

This option lets you find images after inputting multiple keywords, to narrow down and specify your search further.

This is very similar to using quotes when searching for something online.

Aspect Ratio

This feature allows you to search specifically for certain image aspect ratios.

So, if you wanted to see an image that should be wide, tall, panoramic, etc., you can find those images here.

Region

This feature allows you to see which photos are public in a specific part of the world.

 

This makes it easy to pin down photos from places you plan to visit, etc.

Site or Domain

Like a Google site search, use this advanced image search option to limit the results to photos from a particular website URL.

SafeSearch

Enable or disable SafeSearch to block inappropriate content.

File Type

If you are after specific file types, you can pick which image file format Google should look for (e.g., JPGPNGSVG).

Reverse Image Search

By going to google.com and then selecting “images” in the top right corner, you are brought to Google’s reverse image search.

Now, when you select the camera icon, you can then search for other images by uploading an image.

You can either place an image URL or upload your own specific image.

google-reverse-image-search-5eba87f0684f1.png

This is useful for a few different reasons.

Refine & Narrow Your Search

A reverse image search can help you find images that fit a granular set of search criteria, saving you time scrolling through hundreds of images to locate what you’re after.

It helps to refine and narrow your search, creating a better overall user experience.

 

Pinpoint Image Sources

Say you had saved an image of something when you were searching – for instance, an in-end table that you had been interested in.

You saved the image to your computer, however, cannot remember what website you had pulled it from.

Performing a reverse image search can help you to quickly pinpoint the source.

This can save you a lot of time and hassle, for various types of search results.

end-table-image-search-5eba888806439.png

Integrate Advanced Image Search

There are billions of image searches happening every day.

Yet, many don’t know the full functionality and capabilities that Google offers for performing more robust image searches.

Utilizing these capabilities can help you save a significant amount of time, especially when searching for a specific image, or certain parameters that an image needs to meet.

The next time you’re looking for a specific image, take advantage of advanced filters and reverse image search to help you pinpoint what you’re after.\

[Source: This article was published in searchenginejournal.com By Natalie Hoben - Uploaded by the Association Member: Dorothy Allen]

Categorized in Search Engine

Are you wondering how to do a reverse image search on the web? Fear not. This article is made for you. The Internet is a wild place, to say the least. Files come, and files go on a daily base, and it’s not always easy to keep track of everything. There can be various reasons why you’d want to do a reverse image lookup, but whatever your reasons might be, the following steps should walk you through the basics.

How to find image resources by using a reverse search

A reverse search is unlike a normal image search like the one that you might know from Google. Your starting point is that you have an image and want to find out more about it or find more websites that have also used the same or a very similar image.

  1. Load up TinEye in your browser
  2. Upload your image or enter the image URL
  3. Let the search engine do its magic
  4. It’s done, and you can browse the results

TinEye-Reverse-Image-Search-Engine-Picture-Lookup-Free-Web-Tool.jpg

In the example above, I have tried to look up a photo I took during an automotive fair, to see where else it would end up. While the image happens to be under a creative commons license, it is interesting to see who gives proper credit and who does not. If someone does not make their images available under such a license, they might want to sue or press charges for copyright infringement. Using a reverse image search engine such as TinEye would help you to find out where your pictures went and how they were used.

Are there any alternatives for reverse image lookups?

I found TinEye to be quick and user-friendly, but it’s not the only one of its kind out there. Google does also offer a reverse image search, but it is a bit difficult to get to the right menu while you’re on a computer. You can also give the reverse image search by Dupli Checker a try. It will work in a similar fashion but lets you browse the results of Google, Bing, Yandex, TinEye, Sogou, and Baidu instead of using an own technology. The results might take longer to browse through, but it is possible that different engines find different image locations.

Photo credit: The feature image has been done by Diogo Castro. The screenshot shown is owned by TinEye.

 

[Source: This article was published in techacute.com By Christopher Isak - Uploaded by the Association Member: David J. Redcliff]

Categorized in Search Engine

Google is such a powerhouse search engine that it has not only injected itself into our everyday lives, it’s even a verb now.

But just because we Google things a lot doesn’t mean that that we do it as effectively as possible. So here are some tips to help maximise and improve your Google search results.


Dashes

If you want to exclude a word from your search results, put a dash in front of it.

Example

Watch West Wing online -Netflix

Google-Trick-.png

Quotation Marks

Use quotation marks to search an exact set of words, such as song lyrics.

 

Example:

“You must remember this” song

google-quotation.jpg

Asterisk

Speaking of exact swords, what if you can’t remember them all? No problem — just use an asterisk in place of the unknown word/s. Again, this is great for song lyrics or quotes that you may have only half heard. Alternatively, ones that are often misquoted, like below.

Example:

“Play * Sam”

google-asterisk.jpg

Tilde

Use a tilde before a word to include all of its synonyms.

 

Example:

Star Wars ~Presents

As you can see, it has scraped ‘gifts’ as well:

google-presents.jpg

Double Full Stop

Use a double full stop between two numbers to convey ranges. This is handy for pricing, dates and measurements.

Example:

HP Spectre buy $1000..$2000

google-price.jpg

Site: Query

You can search for something within a specific website by using ‘site:’

Example:

John Wick site:gizmodo.com.au

google-john-wick.jpg

Link: Query

You can find sites that have linked to a specific URL through ‘link:’

Example:

link:https://www.gizmodo.com.au/2018/06/theres-a-possible-paypal-scam-happening-in-australia-right-now/

google-link.jpg

Related: Query

If you’re looking for websites that are related to a specific site, you can use ‘related:’

 

Example:

related:boardgamegeek.com

google-related.jpg

Reverse Image Search

This is incredibly handy if you want to find the origin of a photo you have randomly stumbled across on the web. For example, a plate of delicious looking food that you would love to know the recipe for.

Reverse image searching is also great for tracking down original photographers, identifying things (celebrities, flora and fauna, unlabelled clothes or products you want to buy), discovering where your own work may be getting used, and debunking fake social media posts and profiles.

You can do a reverse image search by going into the ‘images’ tab on Google and clicking on the camera icon in the search bar. You can then either upload an image or insert an image address (right click on an image and hit ‘copy image address). Google will then deliver its best guess on the image.

Example:

I went to Pinterest, searched ‘Ramen’ and chose this image:

1db1d6577ad9b645dbdfd39d781e85db.jpg

I then reverse image searched it on Google to find the recipe.

 google-reverse-image.jpg

This post was originally published on March 29, 2019.

[Source: This article was published in gizmodo.com.au By Tegan Jones - Uploaded by the Association Member: Olivia Russell]

Categorized in Search Engine

PimEyes markets its service as a tool to protect privacy and the misuse of images

Ever wondered where you appear on the internet? Now, a facial recognition website claims you can upload a picture of anyone and the site will find that same person’s images all around the internet.

PimEyes, a Polish facial recognition website, is a free tool that allows anyone to upload a photo of a person’s face and find more images of that person from publicly accessible websites like Tumblr, YouTube, WordPress blogs, and news outlets.

In essence, it’s not so different from the service provided by Clearview AI, which is currently being used by police and law enforcement agencies around the world. PimEyes’ facial recognition engine doesn’t seem as powerful as Clearview AI’s app is supposed to be. And unlike Clearview AI, it does not scrape most social media sites.

PimEyes markets its service as a tool to protect privacy and the misuse of images. But there’s no guarantee that someone will upload their own face, making it equally powerful for anyone trying to stalk someone else. The company did not respond to a request for comment.

 

PimEyes monetizes facial recognition by charging for a premium tier, which allows users to see which websites are hosting images of their faces and gives them the ability to set alerts for when new images are uploaded. The PimEyes premium tiers also allow up to 25 saved alerts, meaning one person could be alerted to newly uploaded images of up to 25 people across the internet. PimEyes has also opened up its service for developers to search its database, with pricing for up to 100 million searches per month.

Facial recognition search sites are rare but not new. In 2016, Russian tech company NtechLab launched FindFace, which offered similar search functionality, until shutting it down in a pivot to state surveillance. Founders described it as a way to find women a person wanted to date.

“You could just upload a photo of a movie star you like, or your ex, and then find 10 girls who look similar to her and send them messages,” cofounder Alexander Kabakov told The Guardian.

The PimEyes premium tiers also allow up to 25 saved alerts, meaning one person could be alerted to newly uploaded images of up to 25 people across the internet.

While Google’s reverse image search also has some capability to find similar faces, it doesn’t use specific facial recognition technology, the company told OneZero earlier this year.

“Search term suggestions rely on aggregate metadata associated with images on the web that are similar to the same composition, background, and non-biometric attributes of a particular image,” a company spokesperson wrote in February. If you upload a photo of yourself with a blank background, for example, Google may surface similarly composed portraits of other people who look nothing like you.

PimEyes also writes on its website that it has special contracts available for law enforcement that can search “darknet websites,” and its algorithms are also built into at least one other company’s application. PimEyes works with Paliscope, software aimed at law enforcement investigators, to provide facial recognition inside documents and videos. Paliscope says it has recently partnered with 4theOne Foundation, which seeks to find and recover trafficked children.

There are still many open questions about PimEyes, like exactly how it obtains data on people’s faces, its contracts with law enforcement, and the accuracy of its algorithms.

PimEyes markets itself as a solution for customers worried about where their photos appear online. The company suggests contacting websites where images are hosted and asking them to remove images. But because anyone can search for anyone, services like PimEyes may generate more privacy issues than they solve.

 

[Source: This article was published in onezero.medium.com By Dave Gershgorn - Uploaded by the Association Member: Grace Irwin]

Categorized in Search Engine

An update to Google Images creates a new way for site owners to drive traffic with their photos.

Google is adding more context to photos in image search results, which presents site owners with a new opportunity to earn traffic.

Launching this week, a new feature in Google Images surfaces quick facts about what’s being shown in photos.

Information about people, places or things related to the image is pulled from Google’s Knowledge Graph and displayed underneath photos when they’re clicked on.

image-search.jpeg

More Context = More Clicks?

Google says this update is intended to help searchers explore topics in more detail.

One of the ways searchers can explore topics in more detail is by visiting the web page where the image is featured.

 

The added context is likely to make images more appealing to click on. It’s almost like Google added meta descriptions to image search results.

However, it’s not quite the same as that, because the images and the facts appearing underneath come from different sources.

image-search-1.jpeg

Results in Google Images are sourced from sites all over the web, but the corresponding facts for each image are pulled from the Knowledge Graph.

In the examples shared by Google, you can see how the image comes from the website where it’s hosted while the additional info is taken from another source.

On one hand, that gives site owners little control over the information that is displayed under their images in search results.

On the other hand, Google is giving searchers more information about images that could potentially drive more clicks to the image source.

Perhaps the best part of this update is it requires no action on the part of site owners. Google will enhance your image search snippets all on its own.

Another Traffic Opportunity

If you’re fortunate enough to have content included in Google’s Knowledge Graph, then there’s now more opportunities to have those links surfaced in search results.

Contrary to how it may seem at times, Wikipedia is not the only source of information in Google’s Knowledge Graph. Google draws from hundreds of sites across the web to compile billions of facts.

After all, there are over 500 billion facts about five billion entities in the Knowledge Graph – they can’t all come from Wikipedia.

An official Google help page states:

“Facts in the Knowledge Graph come from a variety of sources that compile factual information. In addition to public sources, we license data to provide information such as sports scores, stock prices, and weather forecasts.

We also receive factual information directly from content owners in various ways, including from those who suggest changes to knowledge panels they’ve claimed.”

As Google says, site owners can submit information to the Knowledge Graph by claiming a knowledge panel.

That’s not something everyone can do, however, as they either have to be an entity featured in a knowledge panel or represent one.

But this is still worth mentioning as it’s low-hanging fruit for those who have the opportunity to claim a knowledge panel and haven’t yet.

Claiming your business’s knowledge panel is a must-do if you haven’t done so already. Local businesses stand to gain the most from from this update.

That’s especially true if yours is the sort of business that would have photos of it published on the web.

 

Then your Knowledge Graph information, with a link, could potentially be surfaced underneath those images.

[Source: This article was published in searchenginejournal.com By Matt Southern - Uploaded by the Association Member: Deborah Tannen]

Categorized in Search Engine

Google is bringing fact check information to image search results worldwide starting today.

Google is adding “Fact Check” labels to thumbnails in image search results in a continuation of its fact check efforts in Search and News.

“Photos and videos are an incredible way to help people understand what’s going on in the world. But the power of visual media has its pitfalls⁠—especially when there are questions surrounding the origin, authenticity or context of an image.”

 

This change is being rolled out today to help people navigate issues around determining the authenticity of images, and make more informed decisions about the content they consume.

When you see certain pictures in Google Images, such as a shark swimming down the street in Houston, Google will attach a “Fact Check” label underneath the thumbnail.

Screenshot 1
Is that image of a shark swimming down a street in Houston real? Google Images now has "Fact Check" labels to help inform you in some cases like this (no, it was not real). Our post today explains more about how & when fact checks appear in Google Images: https://www.blog.google/products/search/bringing-fact-check-information-google-images/ …

EbIVJlCU4AAonJG.jpg

After tapping on a fact-checked result to view a larger preview of the image, Google will display a summary of the information contained on the web page where the image is featured.

A “Fact Check” label will only appear on select images that come from independent, authoritative sources on the web. It’s not exactly known what criteria a publisher needs to meet in order to be considered authoritative.

According to a help page, Google uses an algorithm to determine which publishers are trusted sources.

Google also relies on ClaimReview structured data markup that publishers are required to use to indicate fact check content to search engines.

Fact Check labels may appear both for fact check articles about specific images and for fact check articles that include an image in the story.

 

As mentioned at the beginning of this article, Google already highlights fact checks in regular search results and Google News. YouTube also utilizes ClaimReview to surface fact check information panels in Brazil, India and the U.S.

Google says its fact check labels are surfaced billions of times per year.

While adding ClaimReview markup is encouraged, being eligible to serve a Fact Check label does not affect rankings. This goes for Google Search, Google Images, Google News, and YouTube.

 [Source: This article was published in searchenginejournal.com By Matt Southern - Uploaded by the Association Member: Olivia Russell]

Categorized in Search Engine

Reverse image search is one of the most well-known and easiest digital investigative techniques, with two-click functionality of choosing “Search Google for image” in many web browsers. This method has also seen widespread use in popular culture, perhaps most notably in the MTV show Catfish, which exposes people in online relationships who use stolen photographs on their social media.

However, if you only use Google for reverse image searching, you will be disappointed more often than not. Limiting your search process to uploading a photograph in its original form to just images.google.com may give you useful results for the most obviously stolen or popular images, but for most any sophisticated research project, you need additional sites at your disposal — along with a lot of creativity.

 

This guide will walk through detailed strategies to use reverse image search in digital investigations, with an eye towards identifying people and locations, along with determining an image’s progeny. After detailing the core differences between the search engines, Yandex, Bing, and Google are tested on five test images showing different objects and from various regions of the world.

Beyond Google

The first and most important piece of advice on this topic cannot be stressed enough: Google reverse image search isn’t very good.

As of this guide’s publication date, the undisputed leader of reverse image search is the Russian site Yandex. After Yandex, the runners-up are Microsoft’s Bing and Google. A fourth service that could also be used in investigations is TinEye, but this site specializes in intellectual property violations and looks for exact duplicates of images.

Yandex

Yandex is by far the best reverse image search engine, with a scary-powerful ability to recognize faces, landscapes, and objects. This Russian site draws heavily upon user-generated content, such as tourist review sites (e.g. FourSquare and TripAdvisor) and social networks (e.g. dating sites), for remarkably accurate results with facial and landscape recognition queries.

Its strengths lie in photographs taken in a European or former-Soviet context. While photographs from North America, Africa, and other places may still return useful results on Yandex, you may find yourself frustrated by scrolling through results mostly from Russia, Ukraine, and eastern Europe rather than the country of your target images.

To use Yandex, go to images.yandex.com, then choose the camera icon on the right.

yandex instructions1

From there, you can either upload a saved image or type in the URL of one hosted online.

yandex instructions2 1536x70

If you get stuck with the Russian user interface, look out for Выберите файл (Choose file), Введите адрес картинки (Enter image address), and Найти (Search). After searching, look out for Похожие картинки (Similar images), and Ещё похожие (More similar).

 

The facial recognition algorithms used by Yandex are shockingly good. Not only will Yandex look for photographs that look similar to the one that has a face in it, but it will also look for other photographs of the same person (determined through matching facial similarities) with completely different lighting, background colors, and positions. While Google and Bing may just look for other photographs showing a person with similar clothes and general facial features, Yandex will search for those matches, and also other photographs of a facial match. Below, you can see how the three services searched the face of Sergey Dubinsky, a Russian suspect in the downing of MH17. Yandex found numerous photographs of Dubinsky from various sources (only two of the top results had unrelated people), with the result differing from the original image but showing the same person. Google had no luck at all, while Bing had a single result (fifth image, second row) that also showed Dubinsky.

Screenshot 4

Screenshot 5

Yandex is, obviously, a Russian service, and there are worries and suspicions of its ties (or potential future ties) to the Kremlin. While we at Bellingcat constantly use Yandex for its search capabilities, you may be a bit more paranoid than us. Use Yandex at your own risk, especially if you are also worried about using VK and other Russian services. If you aren’t particularly paranoid, try searching an un-indexed photograph of yourself or someone you know in Yandex, and see if it can find yourself or your doppelganger online.

Bing

Over the past few years, Bing has caught up to Google in its reverse image search capabilities, but is still limited. Bing’s “Visual Search”, found at images.bing.com, is very easy to use, and offers a few interesting features not found elsewhere.

bing visualsearch

Within an image search, Bing allows you to crop a photograph (button below the source image) to focus on a specific element in said photograph, as seen below. The results with the cropped image will exclude the extraneous elements, focusing on the user-defined box. However, if the selected portion of the image is small, it is worth it to manually crop the photograph yourself and increase the resolution — low-resolution images (below 200×200) bring back poor results.

 

Below, a Google Street View image of a man walking a couple of pugs was cropped to focus on just the pooches, leading to Bing to suggest the breed of dog visible in the photograph (the “Looks like” feature), along with visually similar results. These results mostly included pairs of dogs being walked, matching the source image, but did not always only include pugs, as French bulldogs, English bulldogs, mastiffs, and others are mixed in.

bing results cropped 1536x727

Google

By far the most popular reverse image search engine, at images.google.com, Google is fine for most rudimentary reverse image searches. Some of these relatively simple queries include identifying well-known people in photographs, finding the source of images that have been shared quite a bit online, determining the name and creator of a piece of art, and so on. However, if you want to locate images that are not close to an exact copy of the one you are researching, you may be disappointed.

For example, when searching for the face of a man who tried to attack a BBC journalist at a Trump rally, Google can find the source of the cropped image, but cannot find any additional images of him, or even someone who bears a passing resemblance to him.

trumprally

trump results google

While Google was not very strong in finding other instances of this man’s face or similar-looking people, it still found the original, un-cropped version of the photograph the screenshot was taken from, showing some utility.

Five Test Cases

For testing out different reverse image search techniques and engines, a handful of images representing different types of investigations are used, including both original photographs (not previously uploaded online) and recycled ones. Due to the fact that these photographs are included in this guide, it is likely that these test cases will not work as intended in the future, as search engines will index these photographs and integrate them into their results. Thus, screenshots of the results as they appeared when this guide was being written are included.

 

These test photographs include a number of different geographic regions to test the strength of search engines for source material in western Europe, eastern Europe, South America, southeast Asia, and the United States. With each of these photographs, I have also highlighted discrete objects within the image to test out the strengths and weaknesses for each search engine.

Feel free to download these photographs (every image in this guide is hyperlinked directly to a JPEG file) and run them through search engines yourself to test out your skills.

Olisov Palace In Nizhny Novgord, Russia (Original, not previously uploaded online)

test-a-1536x1134.jpg

Isolated: White SUV in Nizhny Novgorod

test-a-suv.jpg

Isolated: Trailer in Nizhny Novgorod

test-a-trailer.jpg

Cityscape In Cebu, Philippines (Original, not previously uploaded online)

test-b-1536x871.jpg

Isolated: Condominium complex, “The Padgett Place

b-toweronly.jpg

Isolated: “Waterfront Hotel

b-tower2only.jpg

Students From Bloomberg 2020 Ad (Screenshot from video)

test-c-1536x1120.jpg

Isolated: Student

c-studentonly.jpg

Av. do Café In São Paulo, Brazil (Screenshot Google Street View)

test-d-1536x691.jpg

Isolated: Toca do Açaí

d-tocadoacai.jpg

Isolated: Estacionamento (Parking)

d-estacionameno-1536x742.jpg

Amsterdam Canal (Original, not previously uploaded online)

test-e-1536x1150.jpg

Isolated: Grey Heron

test-e-bird.jpg

Isolated: Dutch Flag (also rotated 90 degrees clockwise)

test-e-flag.jpg

Results

Each of these photographs were chosen in order to demonstrate the capabilities and limitations of the three search engines. While Yandex in particular may seem like it is working digital black magic at times, it is far from infallible and can struggle with some types of searches. For some ways to possibly overcome these limitations, I’ve detailed some creative search strategies at the end of this guide.

 

Novgorod’s Olisov Palace

Predictably, Yandex had no trouble identifying this Russian building. Along with photographs from a similar angle to our source photograph, Yandex also found images from other perspectives, including 90 degrees counter-clockwise (see the first two images in the third row) from the vantage point of the source image.

a-results-yandex.jpg

Yandex also had no trouble identifying the white SUV in the foreground of the photograph as a Nissan Juke.

a-results-suv-yandex.jpg

Lastly, in the most challenging isolated search for this image, Yandex was unsuccessful in identifying the non-descript grey trailer in front of the building. A number of the results look like the one from the source image, but none are an actual match.

a-results-trailer-yandex.jpg

Bing had no success in identifying this structure. Nearly all of its results were from the United States and western Europe, showing houses with white/grey masonry or siding and brown roofs.

a-results-bings-1536x725.jpg

Likewise, Bing could not determine that the white SUV was a Nissan Juke, instead focusing on an array of other white SUVs and cars.

a-suvonly-bing-1536x728.jpg

Lastly, Bing failed in identifying the grey trailer, focusing more on RVs and larger, grey campers.

a-trailoronly-bing-1536x730.jpg

Google‘s results for the full photograph are comically bad, looking to the House television show and images with very little visual similarity.

a-results-google-1536x1213.jpg

Google successfully identified the white SUV as a Nissan Juke, even noting it in the text field search. As seen with Yandex, feeding the search engine an image from a similar perspective as popular reference materials — a side view of a car that resembles that of most advertisements — will best allow reverse image algorithms to work their magic.

 

a-suvonly-google.jpg

Lastly, Google recognized what the grey trailer was (travel trailer / camper), but its “visually similar images” were far from it.

a-trailoronly-google-1536x1226.jpg

Scorecard: Yandex 2/3; Bing 0/3; Google 1/3

Cebu

Yandex was technically able to identify the cityscape as that of Cebu in the Philippines, but perhaps only by accident. The fourth result in the first row and the fourth result in the second row are of Cebu, but only the second photograph shows any of the same buildings as in the source image. Many of the results were also from southeast Asia (especially Thailand, which is a popular destination for Russian tourists), noting similar architectural styles, but none are from the same perspective as the source.

b-results-yandex.jpg

Of the two buildings isolated from the search (the Padgett Palace and Waterfront Hotel), Yandex was able to identify the latter, but not the former. The Padgett Palace building is a relatively unremarkable high-rise building filled with condos, while the Waterfront Hotel also has a casino inside, leading to an array of tourist photographs showing its more distinct architecture.

 

b-tower1-yandex.jpg

b-tower2-yandex.jpg

Bing did not have any results that were even in southeast Asia when searching for the Cebu cityscape, showing a severe geographic limitation to its indexed results.

b-results-bing-1536x710.jpg

Like Yandex, Bing was unable to identify the building on the left part of the source image.

b-tower1-bing-1536x707.jpg

Bing was unable to find the Waterfront Hotel, both when using Bing’s cropping function (bringing back only low-resolution photographs) and manually cropping and increasing the resolution of the building from the source image. It is worth noting that the results from these two versions of the image, which were identical outside of the resolution, brought back dramatically different results.

b-tower2-bing-1536x498.jpg

b-tower2-bing2-1536x803.jpg

As with Yandex, Google brought back a photograph of Cebu in its results, but without a strong resemblance to the source image. While Cebu was not in the thumbnails for the initial results, following through to “Visually similar images” will fetch an image of Cebu’s skyline as the eleventh result (third image in the second row below).

b-results-google-1536x1077.jpg

As with Yandex and Bing, Google was unable to identify the high-rise condo building on the left part of the source image. Google also had no success with the Waterfront Hotel image.

b-tower1-google-1536x1366.jpg

b-tower2-google-1536x1352.jpg

Scorecard: Yandex 4/6; Bing 0/6; Google 2/6

 

Bloomberg 2020 Student

Yandex found the source image from this Bloomberg campaign advertisement — a Getty Images stock photo. Along with this, Yandex also found versions of the photograph with filters applied (second result, first row) and additional photographs from the same stock photo series. Also, for some reason, porn, as seen in the blurred results below.

c-results-yandex.jpg

When isolating just the face of the stock photo model, Yandex brought back a handful of other shots of the same guy (see last image in first row), plus images of the same stock photo set in the classroom (see the fourth image in the first row).

c-studentonly-results-yandex.jpg

Bing had an interesting search result: it found the exact match of the stock photograph, and then brought back “Similar images” of other men in blue shirts. The “Pages with this” tab of the result provides a handy list of duplicate versions of this same image across the web.

c-results-bing-1536x702.jpg

c-results-bing2.jpg

Focusing on just the face of the stock photo model does not bring back any useful results, or provide the source image that it was taken from.

c-studentonly-results-bing-1536x721.jpg

Google recognizes that the image used by the Bloomberg campaign is a stock photo, bringing back an exact result. Google will also provide other stock photos of people in blue shirts in class.

c-results-google.jpg

In isolating the student, Google will again return the source of the stock photo, but its visually similar images do not show the stock photo model, rather an array of other men with similar facial hair. We’ll count this as a half-win in finding the original image, but not showing any information on the specific model, as Yandex did.

 

c-studentonly-results-google.jpg

Scorecard: Yandex 6/8; Bing 1/8; Google 3.5/8

Brazilian Street View

Yandex could not figure out that this image was snapped in Brazil, instead focusing on urban landscapes in Russia.

d-results-yandex.jpg

For the parking sign [Estacionamento], Yandex did not even come close.

d-parking-yandex.jpg

Bing did not know that this street view image was taken in Brazil.

d-results-bing-1536x712.jpg

…nor did Bing recognize the parking sign

d-parking-bing-1536x705.jpg

…or the Toca do Açaí logo.

d-toco-bing-1536x498.jpg

Despite the fact that the image was directly taken from Google’s Street View, Google reverse image search did not recognize a photograph uploaded onto its own service.

d-results-google-1536x1188.jpg

Just as Bing and Yandex, Google could not recognize the Portuguese parking sign.

d-parking-google.jpg

Lastly, Google did not come close to identifying the Toca do Açaí logo, instead focusing on various types of wooden panels, showing how it focused on the backdrop of the image rather than the logo and words.

 

d-toca-google-1536x1390.jpg

Scorecard: Yandex 7/11; Bing 1/11; Google 3.5/11

Amsterdam Canal

Yandex knew exactly where this photograph was taken in Amsterdam, finding other photographs taken in central Amsterdam, and even including ones with various types of birds in the frame.

e-results-yandex.jpg

Yandex correctly identified bird in the foreground of the photograph as a grey heron (серая цапля), also bringing back an array of images of grey herons in a similar position and posture as the source image.

 

e-bird-yandex.jpg

However, Yandex flunked the test of identifying the Dutch flag hanging in the background of the photograph. When rotating the image 90 degrees clockwise to present the flag in its normal pattern, Yandex was able to figure out that it was a flag, but did not return any Dutch flags in its results.

e-flag-yandex.jpg

test-e-flag2.jpg

e-flag2-yandex.jpg

Bing only recognized that this image shows an urban landscape with water, with no results from Amsterdam.

e-results-bing-1536x723.jpg

Though Bing struggled with identifying an urban landscape, it correctly identified the bird as a grey heron, including a specialized “Looks like” result going to a page describing the bird.

e-bird-bing-1536x1200.jpg

However, like with Yandex, the Dutch flag was too confusing for Bing, both in its original and rotated forms.

e-flag-bing-1536x633.jpg

e-flag2-bing-1536x491.jpg

Google noted that there was a reflection in the canal of the image, but went no further than this, focusing on various paved paths in cities and nothing from Amsterdam.

 

e-results-google-1536x1365.jpg

Google was close in the bird identification exercise, but just barely missed it — it is a grey, not great blue, heron.

e-bird-google-1536x1378.jpg

Google was also unable to identify the Dutch flag. Though Yandex seemed to recognize that the image is a flag, Google’s algorithm focused on the windowsill framing the image and misidentified the flag as curtains.

e-flag-google-1536x1374.jpg

e-flag2-google-1536x1356.jpg

Final Scorecard: Yandex 9/14; Bing 2/14; Google 3.5/14

Creative Searching

Even with the shortcomings described in this guide, there are a handful of methods to maximize your search process and game the search algorithms.

 

Specialized Sites

For one, you could use some other, more specialized search engines outside of the three detailed in this guide. The Cornell Lab’s Merlin Bird ID app, for example, is extremely accurate in identifying the type of birds in a photograph, or giving possible options. Additionally, though it isn’t an app and doesn’t let you reverse search a photograph, FlagID.org will let you manually enter information about a flag to figure out where it comes from. For example, with the Dutch flag that even Yandex struggled with, FlagID has no problem. After choosing a horizontal tricolor flag, we put in the colors visible in the image, then receive a series of options that include the Netherlands (along with other, similar-looking flags, such as the flag of Luxembourg).

flagsearch1.jpgflagsearch2.jpg

Language Recognition

If you are looking at a foreign language with an orthography you don’t recognize, try using some OCR or Google Translate to make your life easier. You can use Google Translate’s handwriting tool to detect the language* of a letter that you hand-write, or choose a language (if you know it already) and then write it out yourself for the word. Below, the name of a cafe (“Hedgehog in the Fog“) is written out with Google Translate’s handwriting tool, giving the typed-out version of the word (Ёжик) that can be searched.

*Be warned that Google Translate is not very good at recognizing letters if you do not already know the language, though if you scroll through enough results, you can find your handwritten letter eventually.

yozhikvtumane.jpg

yozhik-1536x726.jpg

yozhik2-1536x628.jpg

Pixelation And Blurring

As detailed in a brief Twitter thread, you can pixelate or blur elements of a photograph in order to trick the search engine to focus squarely on the background. In this photograph of Rudy Giuliani’s spokeswoman, uploading the exact image will not bring back results showing where it was taken.

2019-12-16_14-55-50-1536x1036.jpg

However, if we blur out/pixelate the woman in the middle of the image, it will allow Yandex (and other search engines) to work their magic in matching up all of the other elements of the image: the chairs, paintings, chandelier, rug and wall patterns, and so on.

blurtest.jpg

After this pixelation is carried out, Yandex knows exactly where the image was taken: a popular hotel in Vienna.

yandexresult.jpg

2019-12-16_15-02-32.jpg

Conclusion

Reverse image search engines have progressed dramatically over the past decade, with no end in sight. Along with the ever-growing amount of indexed material, a number of search giants have enticed their users to sign up for image hosting services, such as Google Photos, giving these search algorithms an endless amount of material for machine learning. On top of this, facial recognition AI is entering the consumer space with products like FindClone and may already be used in some search algorithms, namely with Yandex. There are no publicly available facial recognition programs that use any Western social network, such as Facebook or Instagram, but perhaps it is only a matter of time until something like this emerges, dealing a major blow to online privacy while also (at that great cost) increasing digital research functionality.

 

If you skipped most of the article and are just looking for the bottom line, here are some easy-to-digest tips for reverse image searching:

  • Use Yandex first, second, and third, and then try Bing and Google if you still can’t find your desired result.
  • If you are working with source imagery that is not from a Western or former Soviet country, then you may not have much luck. These search engines are hyper-focused on these areas, and struggle for photographs taken in South America, Central America/Caribbean, Africa, and much of Asia.
  • Increase the resolution of your source image, even if it just means doubling or tripling the resolution until it’s a pixelated mess. None of these search engines can do much with an image that is under 200×200.
  • Try cropping out elements of the image, or pixelating them if it trips up your results. Most of these search engines will focus on people and their faces like a heat-seeking missile, so pixelate them to focus on the background elements.
  • If all else fails, get really creative: mirror your image horizontally, add some color filters, or use the clone tool on your image editor to fill in elements on your image that are disrupting searches.

[Source: This article was published in bellingcat.com By Aric Toler - Uploaded by the Association Member: Issac Avila] 

Categorized in Investigative Research

[This article is originally published in searchengineland.com written by Barry Schwartz - Uploaded by AIRS Member: Alex Gray]

Google is now showing both videos and recipe data within the image search results. This is something Google was testing earlier this year and now seems to have deployed it on mobile search.

Aaron Bradley posted on Google+ that this seems to be derived from newly supported schema around your images. Specifically, you can now mark up your video and recipe content so it is accessible in image search.

The revised video schema page on Google added this line:

 

Your video rich results can also display in image search on mobile devices, providing users with useful information about your video.

Aaron documented how this shows in the search results, and we were able to replicate this ourselves:

google image video watch 1499859346

google image video watch recipe 1499859346

To see this yourself, go to Google on your mobile phone, do a search for the keywords shown above, and click to the image results. Then click on some of the images, and you should see the details listed above.

Categorized in Search Engine

[This article is originally published in searchengineland.com written by Matt McGee - Uploaded by AIRS Member: Bridget Miller] 

Google UK recently shared a list of 52 Things to Do on a variety of Google properties (found via Phil Bradley). It’s a collection of tools and tips about using Google products and services for some everyday functions. If you’re a search power user, you probably know most of them already. But Google’s message seems to be, “Did you know you could do all this stuff on Google?”

It got us thinking about non-Google search tools that might have slipped notice altogether, or just fallen off your radar. With that in mind, here’s a list of seven search tools you may not know about … but should.

 

Read on to discover about how to see search suggestions from all major search engines on one page; a “cover flow” interface to see face images from Google Images; a new way to get recommendations about music, movies and more; new tools to search multiple search engines from one place; a tool for finding hot event tickets and as assist for hunting through Flickr’s many photos.

Soovle

Soovle offers a unique search interface that puts a variety of search sites on a single page. But what makes it unique is that, as you type in the search box, Soovle shows you the auto-completion phrases that each search site recommends. In addition to being original, that function could serve to help with a keyword research project. It looks like this:

Google is the default search site when you arrive, but you can use the right-arrow on your keyboard to quickly select a different site to perform your search. And there’s also a daily update on the top auto-complete terms. Each day, Soovle queries the search sites to find out what they show as the top results for each letter of the alphabet. Pretty cool stuff.

facesaerch

If you like the “cover flow” feature that Apple iTunes offers, you’ll like this new image search engine. facesaerch (yes, “a” before “e”) takes a Google image search, eliminates everything but faces, and gives the results a more modern interface. It looks like this:

It’s nothing groundbreaking overall, but one nice addition is a customizable widget that lets you embed a facesaerch widget on your blog or web page, complete with cool thumbnail scrolling and all. (For your Oprah Winfrey fan page, of course.)

TasteKid

TasteKid is more of a recommendation engine than a search engine. It covers movies, music, and books, offering suggestions for things you might like based on what you search for. The interface is gorgeous (albeit a bit dark/goth), and the recommendations are generally good. Search for U2, for example, and TasteKid suggests you try out INXS, R.E.M., Sting, Bruce Springsteen, Coldplay, and several other artists — most of which fit what a typical U2 fan might enjoy.

There are question marks next to each recommendation. When you mouseover a question mark, TasteKid displays additional information from Wikipedia, YouTube, and Amazon about that artist (or book, movie, actor, etc.). It uses Google Gadgets to offer a widget that can be embedded into your web page or blog.

Fasteagle is a combination search tool and web directory rolled into one interface, with a little touch of feed reader built in, too. The home page gives you quick access to search a dozen different sites, from Google to Delicious to eBay to FriendFeed.

 

It would be nice to be able to customize those 12 options, or add more to the original 12 to make your own personal search portal. But I don’t see that option anywhere on fasteagle, which is still in beta. Meanwhile, clicking on the categories in the top menu (Tools, News, Business, etc.) leads to new sets of sub-categories in the left-side menu. Under the Tech category, for example, the left menu changes to show sub-categories such as Web World, Tech Vloggers, IT News, Computing, Apple, Google, Mobile Computing, and Web Marketing. That last sub-category includes sites like Search Engine Land, Marketing Pilgrim, Search Engine Watch, and several others. Click on any link, and the site shows up in the main fasteagle window, with the top and side menus still showing — making fasteagle almost like a feed reader that gives you quick access to hundreds of web sites in rapid succession.

FanSnap

Have you searched for event tickets lately? It's not fun, and it's not easy. FanSnap hopes to change that by providing a one-stop source for finding tickets to sporting events, theatre productions, and concerts.

FanSnap doesn’t sell tickets; it lets you find tickets being sold by brokers and others in the secondary ticket market. At the moment, I don’t see inventory from official ticket sellers such as Ticketmaster or TicketsWest. They get inventory from more than 50 ticket resellers, making it a much easier way to shop than visiting the individual web sites of that many ticket brokers. To borrow a comparison Om Malik recently made, it’s like Zillow for event tickets.

compfight

Strange name for a Flickr image search engine, but don’t let it keep you away. Compfight offers a handful of customizations that help you drill down into Flickr’s enormous pool of user-uploaded photos.

You can search the full text of a photo page (title, description, and tags), or if that’s producing too many matches, you can just search tags. You can search for photos that allow Creative Commons commercial usage. You can search for photos that are original to Flickr. You can also turn Flickr’s Safe Search on or off. And you can combine all these options in any search combination you want. And rather than Flickr’s clunky, default, 10-at-a-time search results, you get dozens of thumbnails with compfight.

Kedrix

There are plenty of meta-search engines out there, but only one that wants you to “mearch” instead of “search.” That one is Kedrix, which is trying to coin a new word based on the words “meta” and “search.” That doesn’t work for me, but the search engine does, thankfully.

The Kedrix premise is simple: It’s actually not a meta-search engine in the traditional sense. Rather than mash results from different search engines together (as Metacrawler, Dogpile, Mamma, and others do), Kedrix separates the results from the four main search engines on tabs. Google results are all under one tab, Yahoo under another, and so forth. In that sense, it’s more like a search engine comparison tool. And that makes it somewhat more valuable to SEOs (who like to compare results across different engines) than your standard meta-search engine.

Categorized in Search Engine
Page 1 of 3

airs logo

Association of Internet Research Specialists is the world's leading community for the Internet Research Specialist and provide a Unified Platform that delivers, Education, Training and Certification for Online Research.

Get Exclusive Research Tips in Your Inbox

Receive Great tips via email, enter your email to Subscribe.

Follow Us on Social Media

Finance your Training & Certification with us - Find out how?      Learn more