This system employs texture analysis via a Gabor filter bank, CIE Lab space color histogram, and structural analysis using perceptual grouping principles.

CIS is a semantics-based image search engine developed at Vision Research Lab at UCSB. Instead of using a bottom up method, CIS utilizes a top-down approach to categorize images semantically.

This demo allows you to process your own images via the web. Tools include Stereo images, Segmentation, Zerocrossings, Contourlines, Histogram-Transformations, Color-Separations, Anaglyph Creation, Principal Components.

Image segmentation demo from Isis (Intelligent Sensory Information Systems) research group at University of Amsterdam.

Large-scale content-based image retrieval by James Wang, Jia Li, and Gio Wiederhold. Uses wavelets to Classify web sites and web images.