Idée Inc, a Toronto-based company, has announced that it has built a new search engine that employs true image recognition.  Currently in private beta, Idée claims:

“TinEye is the first image search engine on the web to use image identification technology. Given an image to search for, TinEye tells you where and how that image appears all over the web—even if it has been modified.

Just as you are familiar with entering text in a regular search engine such as Google to find web pages that contain that text, TinEye lets you submit an image to find web pages that contain that image.”

The company released a widget that demonstrates some of the algorithm’s findings:

While I am excited to see progress being made toward moving search algorithms beyond text, I question the utility of such an application.  TinEye relies on images as its search query.  When a user uploads a picture, the program creates a digital “fingerprint” for it.  Then, it compares this fingerprint against its index (said to be rapidly growing).  The results, in theory, are exact or near-matches of the searched image.

Image to image search isn’t new.  I worked for a company in 2000-2001 doing the same thing (never publicly released as a search engine), and not just for images (also video and audio).  The problem this company will have is the same as our problem was then— the application, while cool and novel, has no real practical purpose beyond copyright protection.  According to the company, uses for TinEye include:

Find out where and how an image appears online

Research products using a product photo

Find modified versions of unmodified images or vice versa

Research the usage of editorial or stock images

Get international, multilingual websites in your search results

Research corporate imagery or brand usage online

Use a webcam to digitize any image and search for it on the web

Search for your images to see where they are being used

Yes, copyright protection is important and valuable, even if less so for images than for other media (movies, music).  So, maybe they stand a chance serving a relatively niche market.  But, other than being interesting to try once, this doesn’t solve the bigger issue of providing a useful new feature for mass audiences to adopt.

How can a company create a truly useful utility out of recognition-based image search, you ask?

Build a method for generating, validating, and maintaining textual data to accurately describe each “fingerprint”.  Only then can the search query move beyond uploading an image, and starting to use words instead.  Only then will the mass public find it appealing, and adoption of the new technology can begin.  Google’s started on this using their Image Labeler game.  But, with millions upon millions of images on the web, this method of collecting meta data isn’t scalable or effective.  Perhaps the best bet is using meta data collected from image collection management software/services, such as Picasa or Flickr.  But, without validation (something Image Labeler is successful in achieving), such a process would certainly be plagued with bad data and prone to manipulation. 

Either way, I wish Idée Inc the best of luck and really hope they succeed.  We are definitely overdue to start thinking about how search can move past text-text, and on to other useful applications like text-image or text-video.