Principal component analysis for feature extraction of image sequence
This paper presents a method to extract features by PCA (Principal component analysis) from a series of woods surfaces images. The method introduces a principal component subspace and can reserve original information while extraction mainly information. The emulated results show that we can fuse the image series and extract features from the four images of a same surface by using this method. After processing the sequences of images, we get a feature which is good for the next classification and recognition process.
woods surface inspection image series defects detection features extraction Principal component analysis component
Binjie Xiao
Department of Control Science and Engineering College of Electronics and Information Engineering 200092, Shanghai, China
国际会议
成都
英文
250-253
2010-06-12（万方平台首次上网日期，不代表论文的发表时间）