Image hashing with color vector angle

Color vector angle (CVA) is an important feature of processing color images and has been successfully developed and used in real applications, such as edge detection, indexing and retrieval of images. However, it is unsolved how to apply the CVA to efficiently generating an image hash. Also, most image hashing algorithms choose luminance component of color image for hash generation and cannot well capture the color information of images. To tackle these issues, we study efficient image hashing algorithms with the histogram of CVAs, called HCVA hashing. The histogram is first extracted from those angles that are in the biggest circle inscribed inside the normalized image. And then, it is compressed to make a short hash. We conducted some experiments to assess the performance, and illustrated that the DCT (Discrete Cosine Transform) is the best one of that cooperating with HCVA at generating hashes, as well as the HCVA hashing is robust and promising.