An Improved Color Cooccurrence Matrix Texture Descriptor
Xu Shao · 2013
Utilizing similarity measure defined by the fuzzy continuous t-norm operator to describe the degree of difference between pixels in color images,an improved color cooccurrence matrix texture descriptor is proposed.In accordance with the predefined interval of distances and directions,the multi-channel color information of original color image is effectively integrated and converted to pseudo-gray images.Then,gray level cooccurrence matrix (GLCM) texture method is used to extract feature vector for the pseudo-gray image.A large number of experiments are performed on the content-based image retrieval prototype platform and the results show that compared with other types of texture descriptors,the improved texture descriptor has the same feature vector dimension as the GLCM descriptor,while its description ability matches with all kinds of color cooccurrence matrix descriptor.The improved texture descriptor effectively achieves the integration of texture and color characteristics and improves the image retrieval performance.