Title
Corner detector using invariant analysis
Abstract
Corner detection has been shown to be very useful in many computer vision applications. Some valid approaches have been proposed, but few of them are accurate, efficient and suitable for complex applications (such as DSP). In this paper, a corner detector using invariant analysis is proposed. The new detector assumes an ideal corner of a gray level image should have a good corner structure which has an annulus mask. An invariant function was put forward, and the value of which for the ideal corner is a constant value. Then, we could verify the candidate corners by compare their invariant function value with the constant value. Experiments have shown that the new corner detector is accurate and efficient and could be used in some complex applications because of its simple calculation.
Year
DOI
Venue
2013
10.1117/12.2030539
Proceedings of SPIE
Keywords
Field
DocType
corner detect,invariant analysis,invariant function
Digital signal processing,Corner detection,Algorithm,Annulus (oil well),Invariant (mathematics),Gray level,Geometry,Detector,Mathematics,Corner detector
Conference
Volume
Issue
ISSN
8878
null
0277-786X
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Chengfei Zhu122.73
Shuxiao Li2428.97
Yi Song322.07
Hongxing Chang4407.12