DocumentCode :
479971
Title :
Harris Correlation Descriptor (HCD): A Novel Descriptor for Point Matching
Author :
Wang, X.G. ; Wu, F.C. ; Wang, Z.H.
Author_Institution :
Nat. Lab. of Pattern Recognition, Chinese Acad. of Sci., Beijing
Volume :
2
fYear :
2008
fDate :
12-14 Dec. 2008
Firstpage :
1154
Lastpage :
1157
Abstract :
In this paper, a novel descriptor for point matching, called Harris correlation descriptor (HCD), is proposed. Inspired by the Harris feature detector, we use the Harris correlation measure defined with the determinant and trace of the Harris correlation matrix to characterize the gradient distribution in a neighborhood of feature points, and then construct the HCD descriptor which is invariant to image rotation and linear change of intensity. The using of the gradient mean in the Harris correlation measure makes the HCD descriptor not sensitive to the estimated main orientation of feature points, thus robust to image rotation. Moreover, the HCD descriptor has also a good adaptability to other image transformations.
Keywords :
computer vision; correlation methods; gradient methods; image matching; Harris correlation descriptor; Harris correlation matrix; Harris feature detector; gradient distribution; image rotation; image transformations; point matching; Automation; Computer science; Computer vision; Detectors; Filters; Laboratories; Pattern matching; Robustness; Rotation measurement; Software engineering; HCD; Harris Correlation; Point Matching;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Software Engineering, 2008 International Conference on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-0-7695-3336-0
Type :
conf
DOI :
10.1109/CSSE.2008.1313
Filename :
4722257
Link To Document :
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