A Multi-scale Phase Feature Based Method for Image Retrieval

One related key issue in Content Based Image Retrieval (CBIR) is the representation of image visual content. However, traditional image features such as color, shape and texture are not capable of representing the visual content completely. So as to improve the retrieval accuracy, an image retrieval method based on Multi-scale Phase Feature (MPF) is proposed according to the human vision. Firstly, scale space theory is adopted here to decompose the image into Multi-scale Description (MD). And then the global statistical MPF is acquired by histogram projection from the multi-scale phase information, which is extracted by complex steerable filtering of MD. Finally, experiments on general purpose database COREL 5,000 demonstrate that the proposed MPF has a no less than 5% accuracy improvement over classic color features, and it also effectively complements classic color features.