DocumentCode :
2647791
Title :
Image matching by eigen template method for multi-class classification
Author :
Yata, Koshiro ; Koutaki, Gou ; Uchimura, Keiichi
Author_Institution :
Kumamoto Univ., Kumamoto, Japan
fYear :
2015
fDate :
28-30 Jan. 2015
Firstpage :
1
Lastpage :
4
Abstract :
An Image matching technique of target objects recognition and detection is widely used in industrial image processing. In this paper, the authors proposed eigen template method for two dimentional target objects recognition and detection. We have proposed eigen template method of applying the principal component analysis (PCA) to image matching. Also, the authors have proposed to edge based eigen templates method for robust and efficient image matching. These methods can estimate target objects position and pose from two dimensional images. In this paper, eigen template method is extended to the method that can classify multi-class target objects. Our experiment showed that the proposed method can recognize multi-class target objects and estimate position and pose. And the authors showed that the proposed method can efficient image match compared with the previous methods.
Keywords :
eigenvalues and eigenfunctions; image classification; image matching; object detection; object recognition; pose estimation; principal component analysis; PCA; eigen template method; image matching; multiclass classification; pose estimation; position estimation; principal component analysis; two dimensional target object detection; two dimensional target object recognition; Correlation; Estimation; Image edge detection; Image matching; Mathematical model; Object recognition; Principal component analysis; eigen template method; image matching; multi-clsss classification; principal component analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Frontiers of Computer Vision (FCV), 2015 21st Korea-Japan Joint Workshop on
Conference_Location :
Mokpo
Type :
conf
DOI :
10.1109/FCV.2015.7103708
Filename :
7103708
Link To Document :
بازگشت