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Published in:
2015 | OriginalPaper | Chapter
Corner Detection Algorithm with Improved Harris
Authors : Li Wan, Zhenming Yu, Qiuhui Yang
Published in: Advances in Image and Graphics Technologies
Publisher: Springer Berlin Heidelberg
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Traditional algorithm of Harris needs to select a parameter for computing interest values of pixels, and its recognition ability for some types of corners is poor. To solve this problem, this paper proposes a corner detection method which is based on local standard deviation and logarithmic computing. The method decreases effecting to the response values of corners that near the candidate interested points through computing the logarithms of gradient, so it can detect different types of corner more effectively. It can redefine the interest value function according to the statistical features of the standard deviation to decide the corners. The function could avoid selecting value of parameters by person, and it could directly judge whether a candidate interested point is a corner, to make the algorithm has a higher objectivity. The experimental results show that the method can effectively detect the corners of various types, and it can achieve a more accurate effect of positioning.