Color and Geometry as Cues for Indexing
Markus A. Stricker · 1992
This article introduces a new indexing technique based on boundary histograms. For multicolored objects boundary histograms record estimates of the boundary lengths between different discrete colors in an image. Boundary histograms are small and insensitive to noise. To identify images we apply a match function to their boundary histograms. The match function that we derive handles occlusions and distracting pixels in the background of an object gracefully. The robustness and the low complexity of the match function together with its ability to distinguish many objects allow us to use boundary histograms as an index for large image databases. Test results illustrate the above mentioned features of boundary histograms and the match function. Keywords: Object recognition, color indexing, image signature, boundary length estimates. 1 Introduction Recent advances in data storage and data compression will allow image databases to explode in size. However, currently there exist only very ...