Color Object Retrieval Using Local Features Based On Opponent-Process Theory

Although the color is perceived as an irreplaceable element describing the world around us, the techniques for extracting of the local features are mostly based on the description of the intensities while the color information is being fully ignored. This paper proposes a method for extracting of the local features of the color image. As a basic model we have chosen the approach to the human visual system using chromatic opponent channels and the SIFT (Scalable Invariant Feature Transform) method. The idea of this solution is the incorporation of the opponent chromatic channels by replacing the grayscale information in the SIFT method, so that the key points are detected on two separate opponent channels. For the interesting points found in the two channels, the descriptors are formed which are then united into one set. We also propose the new methods for the validation of the keypoint pairing utilizing the keypoint orientation consistency check. The algorithm was tested in an object retrieval experiment.