In content-based image retrieval, the representation of local properties in an image is one of the most active research issues. This paper proposes 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. Color moments and Gabor features around the salient regions in every annular region are computed as feature vectors used for indexing the image. We have tested the proposed scheme using a wide range of image samples from the Corel Image Library for content-based image retrieval. The experiments indicate that the method has produced promising results.