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Volume & Issue no: Volume 4, Issue 1, January 2015

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Title:
Local Information Based Approach to Corner Detection
Author Name:
Ambar Dutta
Abstract:
ABSTRACT For many years feature detection has played an important role in computer vision. In computer vision, the corners of an object play a vital role as features for shape representation and analysis. But corner detection, particularly in real scenes, is still a challenge. In this paper, an improvement to existing corner detection algorithms is presented using information theory where corner detection algorithm is applied to only those regions containing more information that is more intensity variations. The proposed approach substantially reduces the computational time as well as reduces the number of false positive corners. The experimental results are provided to illustrate the effectiveness of the algorithm. Keywords: Corner detection, information content, performance measures, region, threshold
Cite this article:
Ambar Dutta , " Local Information Based Approach to Corner Detection" , International Journal of Application or Innovation in Engineering & Management (IJAIEM) , Volume 4, Issue 1, January 2015 , pp. 186-190 , ISSN 2319 - 4847.
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