Image Retrieval Based on Clustering of Salient Points

In content-based image retrieval, how to representation of local properties in an image is one of the most active research issues. In certain circumstance, however, users concern more about objects of their interest and only wish to retrieve images containing relevant objects, while ignoring irrelevant image areas (such as the background). Previous work on represent of local properties normally requires complicated segmentation of the object from the background. In this paper, we propose an improved salient points detector based on wavelet transform; it can extract salient points in an image more accurately. Then salient points are clustered into different salient regions according to their spatial distribution. It takes not only local image features into account, but also the spatial distribution information of the salient regions. 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.