Color texture moments for content-based image retrieval

In this paper, we adopt local Fourier transform as a texture representation scheme and derive eight characteristic maps for describing different aspects of co-occurrence relations of image pixels in each channel of the (SVcosH, SVsinH, V) color space. Then we calculate the first and second moments of these maps as a representation of the natural color image pixel distribution, resulting in a 48-dimensional feature vector. The novel low-level feature is named color texture moments (CTM), which can also be regarded as a certain extension to color moments in eight aspects through eight orthogonal templates. Experiments show that this new feature can achieve good retrieval performance for CBIR.