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An improved corner detection method based on grayscale changes of image neighboring(PDF)


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An improved corner detection method based on grayscale changes of image neighboring
YANG Jiahao DONG Jingjing YUAN Tong HE Yuheng YANG Dan SHI Meihong
School of Computer Science, Xi’an Polytechnic University, Xi’an 710600, China
corner detection grayscale change Harris algorithm SUSAN algorithm
TP 391
Aiming at the problems of corner detection accuracy or anti-noise performance for classical corner detection algorithms, according to the distribution characteristics of X,T and Y corners,an improved corner detection method based on grayscale changes of image neighboring was proposed.Firstly screening the corner by autocorrelation of image grayscale changes. Then, traversing and screening the corner set by USAN(Univalue Segment Assimilating Nucleus)template.Based on the distribution dispersion in the template, the corner points are located twice. Finally the nonmaximum suppression method was used to locate corner accurately.Corner detection was made by the simulated geometric images and real images,and compared with Harris algorithm,SUSAN algorithm and grayscale difference and template based Harris algorithm.The results show that the accuracy and consistency of the improved corner dection method are enhanced obviously,and the method has better comprehensive detection property.


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Last Update: 2019-10-07