2D color shape recognition using Zernike moments

2D Zernike moments belong to the useful object invariant descriptors which have been successfully applied in pattern recognition tasks. The main problem of using Zernike moments invariants is that they are not able to discriminate two objects having the same shape. In this paper, an approach based on Zernike moments applied on color images is proposed. A support vector machine is used for object classification. For object segmentation, the connected component labeling algorithm is used. Compared with the classical method, this approach shows higher accuracy in object recognition. Some experimental results on the COIL-100 database are presented.