Scene Classification Based on Gray Level-Gradient Co-Occurrence Matriz in the Neighborhood of Interest Points
Scene classification is an important application field of multimedia information technology, whereas how to extract features from image is one of the key technologies in scene classification and recognition. A new method of extracting features is presented in this paper, it extracts features through gray levelgradient co-occurrence matrix in the neighborhood of interest points, also it can reserve the key image edge information, and it is called GGNP for short in the paper. The weighted Gowers similarity coefficient model is adopted as the basis for image scene classification, as it is more flexible than Euclidean distance function. Compared with traditional methods, the method has a good invariance in image scaling, rotation, translation and robust across a substantial range of affine distortion, meanwhile having good real-time. Experimentations are designed to test the precision and time-consuming of the method, the results of experiments show that the method has good effects on scene classification.
interest points scene classification gray level-gradient co-occurrence matriz local feature vector.
Shuo Chen Chengdong Wu Dongyue Chen Wenjun Tan
College of Information Science & Engineering Northeastern University Shenyang,China
国际会议
上海
英文
3011-3014
2009-11-20（万方平台首次上网日期，不代表论文的发表时间）