In content-based image retrieval, the representation of local properties in an image is one of the most active research issues. This paper introduces a salient region detector based on wavelet transform. The detector can extract the visually meaningful regions on an image and reflect local characteristics. An annular segmentation algorithm based on the distribution of salient regions is designed. It takes not only local image features into account, but also the spatial distribution information of the salient regions. Then, Color moments and the introduced visual perception texture features of the regions around the salient points were computed as a features vector used for indexing the image. We tested the proposed scheme using a wide range image samples from the Corel Image Library, the experimental results indicating that the method has produced promising results.