On illumination invariance in color object recognition

摘要

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 differ from those that are 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 different 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 filtering for efficiency. 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.