关键词: 场景分类, 多尺度, 统计特征, 协同表示

Abstract: In order to solve the problem of insufficient information provided by a single feature in complex scene recognition, a multi-scale census transform of difference of distant neighbors feature is proposed. Gabor filtering is used to obtain the multi-scale feature information of the image, and the improved census transform of difference of distant neighbors feature is extracted from the original image and the Gabor filtered image to generate a multi-scale descriptor. Finally, the multi-scale census transform features and bag-of-visual-word (BOVW) features are merged by kernel collaborative representation to classify scenes. This method considers the scale information and the long distance point information, and solves the problem of low discrimination of a single feature. The algorithm is verified on two standard datasets, and the experimental results show that the recognition rate of the proposed method is better.

Key words: scene classification, multi-scale, statistical features, collaborative representation