Research on Commodity Image Classification Based on Local Oppugnant Color Vector Angle Pattern

Based on the existing commodity image classification research, there is a lack of the use of the most recent color and texture features of the combination of commodity image classification. According to the local oppugnant color vector angle pattern (LOCVAP) feature extraction algorithm and the Deep Believe Network (DBN) classifier, the image classification is simulated and analyzed. The experimental results show that the results of LOCVAP descriptor have a greater improvement than those of other subcategories of feature descriptors.