DocumentCode
2255710
Title
Harris feature vector descriptor
Author
Wang, Xu-guang ; Su, Jie ; Cheng, Hai-yan
Author_Institution
Dept. of Autom., North China Electr. Power Univ., Baoding, China
Volume
1
fYear
2010
fDate
11-14 July 2010
Firstpage
512
Lastpage
517
Abstract
This paper defines a new image feature called Harris feature vector, which is able to describe the image gradient distribution in an effective way. By computing the mean and the standard deviation of the Harris feature vector in a local image region, novel descriptors are constructed for feature matching which are invariable to image rigid transformation and linear intensity change. Experimental evidence suggests that the novel descriptor for point matching has a good adaptability to slight view point changing, JPEG compression and nonlinear changing of intensity, besides, the descriptor for line matching performs well too.
Keywords
data compression; feature extraction; gradient methods; image coding; image matching; Harris feature vector descriptor; JPEG compression; feature matching; image gradient distribution; image rigid transformation; linear intensity change; local image region; Cybernetics; Detectors; Feature extraction; Image coding; Machine learning; Transform coding; Vectors; Feature descriptor; Feature matching; HFV; Orthogonal transformation;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics (ICMLC), 2010 International Conference on
Conference_Location
Qingdao
Print_ISBN
978-1-4244-6526-2
Type
conf
DOI
10.1109/ICMLC.2010.5581008
Filename
5581008
Link To Document