DocumentCode :
3437741
Title :
Corner detection using support vector machines
Author :
Banerjee, Minakshi ; Kundu, Malay K. ; Mitra, Pabitra
Author_Institution :
Machine Indian Stat. Inst., Kolkata, India
Volume :
2
fYear :
2004
fDate :
23-26 Aug. 2004
Firstpage :
819
Abstract :
A support vector machine based algorithm for corner detection is presented. It is based on computing the direction of maximum gray-level change for each edge pixel in an image, and then representing the edge pixel by a four dimensional feature vector constituted by the count of other edge pixels lying in a window centred about and having each of the possible four directions as their direction of maximum local gray-level change. A support vector machine is designed using this feature vectors and the support vectors, representing critical points in a classification problem, correspond to the corner points. The algorithm is straightforward and does not involve computation of complex differential geometric operators. It has implicit learning capability resulting in good performance for a wide range of images.
Keywords :
image classification; image resolution; support vector machines; corner detection; differential geometric operators; image edge pixel; maximum gray-level change; support vector machines; Autocorrelation; Change detection algorithms; Detectors; Geometry; Humans; Image edge detection; Pixel; Shape; Support vector machine classification; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on
ISSN :
1051-4651
Print_ISBN :
0-7695-2128-2
Type :
conf
DOI :
10.1109/ICPR.2004.1334384
Filename :
1334384
Link To Document :
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