The program was created last spring and I have just been sitting on it – no time. You create a collection of images and PxSearch can search for pictures similar to the one that you choose.

This is not even a prototype; it is in fact a test program. This is why every time you add an image to the collection, a few of its versions (rotated, blurred, etc) are also added and analyzed. This feature is needed to help you see when the algorithm works well and when it does not. The idea is that these versions of the image have to appear near the top of the list of similar images. It works reasonably well, with some images. The appropriate image have to be of good quality, with several larger objects, little pixelation, noise etc. Faces, simple landscapes, some medical images work. Fingerprints don’t. But I think many more would work if the thumbnails were larger. Computation isn’t fast in the first place and then analyzing extra 7 versions of the image takes extra time. So, unfortunately, I had to shrink the images to 100×100 to make the processing time reasonable.

The program is available upon request. Keep in mind that you will need at least a few dozen images in the collection to appreciate the algorithm. But to seriously test it, you’d need at least thousands. This is why I want to put it online as soon as possible.

The algorithm is very unsophisticated. It is based on Pixcavator and simply computes distributions of objects of each size. That’s what the “signatures” are. To match two images, their signatures are compared by a simple formula (weighted sum of differences). The end result is not a search based on “likeness” (it’s been done, badly), but on a quantifiable similarity. Basically, it’s about finding copies of a given image. This may have something to do with copyright filtering. More information will be added to the article on Image Search in the wiki. There are a few visual image search engine listed in that article. They didn’t impress me technologically, but those that work are surely fun to use. So is this one.