DocumentCode
525986
Title
Defects detection based on principal component analyses and support vector machines
Author
Xiao, Binjie
Author_Institution
Dept. of Control Sci. & Eng., Coll. of Electron. & Inf. Eng., Shanghai, China
Volume
2
fYear
2010
fDate
12-13 June 2010
Firstpage
296
Lastpage
299
Abstract
Woods are used in many fields. The appearance of woods is important for the quality of wood products. In this paper, we present an image series fusion method based principal component analyses and recognize the defects by support vector machines. We select the histogram of the feature image as feature vector, and send it to support vector machines for recognition and classification. The results show that this method can fuse the image series and detect the defects.
Keywords
feature extraction; image fusion; image recognition; principal component analysis; support vector machines; wood; defect recognition; defects detection; feature image histogram; image series fusion method; principal component analyses; support vector machines; wood appearance; wood product quality; Image series Fusion; Principal component analyses; Support vector machines; defects detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer and Communication Technologies in Agriculture Engineering (CCTAE), 2010 International Conference On
Conference_Location
Chengdu
Print_ISBN
978-1-4244-6944-4
Type
conf
DOI
10.1109/CCTAE.2010.5544326
Filename
5544326
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