Feature Extraction and Classification of Images Based on Corner Invariant Moments
Xue Ming Zhai, Dong Ya Zhang, Yu Jia Zhai, Ruo Chen Li, De Wen Wang · Applied Mechanics and Materials · 2013
Image feature extraction and classification is increasingly important in all sectors of the images system management. Aiming at the problems that applying Hu invariant moments to extract image feature computes large and too dimensions, this paper presented Harris corner invariant moments algorithm. This algorithm only calculates corner coordinates, so can reduce the corner matching dimensions. Combined with the SVM (Support Vector Machine) classification method, we conducted a classification for a large number of images, and the result shows that using this algorithm to extract invariant moments and classifying can achieve better classification accuracy.