2D Pixel Trigrams for Content-Based Image Retrieval

The problem of finding similar images and images with a similar sub-image given a search image or part of a search image is addressed in this article by using 3×3 local pattern statistics in thresholded gradient images of scanned portraits normalized for scale, orientation, position and lighting. Pattern frequencies sorted on magnitude are closely linked to a spatial frequency ordering. The 2D trigram feature vector is formed by a weighing of the pattern frequencies. Several weighing functions were applied to a database of 3014 image files: the results indicate that a sort of band pass approach, suppressing both ends of the sorted pattern frequency distribution works best. The method works well on full image comparison and will be applied to sub-image search in the near future.