An Effective Visual Descriptor Based on Color and Shape Features for Image Retrieval

In this paper we present a Content-Based Image Retrieval (CBIR) system which extracts color features using Dominant Color Correlogram Descriptor (DCCD) and shape features using Pyramid Histogram of Oriented Gradients (PHOG). The DCCD is a descriptor which extracts global and local color features, whereas the PHOG descriptor extracts spatial information of shape in the image. In order to evaluate the image retrieval effectiveness of the proposed scheme, we used some metrics commonly used in the image retrieval task such as, the Average Retrieval Precision (ARP), the Average Retrieval Rate (ARR) and the Average Normalized Modified Retrieval Rank (ANMRR) and the Average Recall (R)-Average Precision (P) curve. The performance of the proposed algorithm is compared with some other methods which combine more than one visual feature (color, texture, shape). The results show a better performance of the proposed method compared with other methods previously reported in the literature.