On illumination invariance in color object recognition

Several color object recognition methods that are based on image retrieval algorithms attempt to discount changes of illumination in order to increase performance when test image illumination conditions di er from those that obtained when the image database was created. Here we investigate under what general conditions illumination change can be described using a simple linear transform among RGB channels, for a multi{colored object, and adduce a di erent underlying principle than that usually suggested. The resulting new method, the Linear Color algorithm, is more accurately illuminant{invariant than previous methods. An implementation of the method uses a combination of wavelet compression and DCT transform to fully exploit the technique of low{pass ltering for e ciency. Results are very encouraging, with substantially better performance than other methods tested. The method is also fast, in that the indexing process is entirely carried out in the compressed domain and uses a feature vector of only 63 integers.