Multi-feature content-based product image retrieval based on region of main object

Content-based image retrieval (CBIR) has got an intense interest and seen considerable progress over the last decade. But most of the time it is only applied in laboratory. One important reason for this is the diversity of images. Different practical situations call for different taxonomy definitions of images, and lead to very different solutions. At present, and even in the foreseeable future, a general purpose CBIR system is not really possible. However, image search engines oriented at specific domains are feasible in technology and also have the actual demand. With the rapid development of electronic commerce, searching specific product by image has become one of the most attractive related research topics. In this paper, we propose a region-based method fit for the content-based retrieval of product images. The method focuses on two key issues: fast extraction of the main region, in which the product locates, as well as efficient shape and color features extraction. To show the validity of the proposed region-based method, compared experiments are carried out and illustrated on the PI 100 dataset.