New image retrieval approach based on interest points

Content-based image retrieval (CBIR) is becoming a hot research point in the field of multimedia information retrieval. Interest points are local features with high informational content. So, this paper proposes a novel method for image retrieval using interest points, which contains three key stages: interest points detection, image features description based on interest points and similarity measure between two images. In the process of detecting interest points, firstly, we use a self-adaptive filter to smooth image, and then use detector to find interest points. In the stage of image features description, we design a 3D histogram to represent image, which contains local gray changes of interest points, mutual position relations among interest points and interest points distribution of the whole image. In the stage of similarity measure, we use the distance between two 3D histograms to calculate similarity between two images. Lots of experimental results based on a database containing 1500 images demonstrate our proposed approach is efficient.