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《Journal of University of Chinese Academy of Sciences》 2016-01
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Target edge detection based on SUSAN operator and corner discriminant factor

WU Yiquan;WANG Kai;College of Electronic and Information Engineering,Nanjing University of Aeronautics and Astronautics;Provincial Key Laboratory of Manufacturing and Automation;Shenzhen Key Laboratory of Urban Rail Traffic;Jiangsu Key Laboratory of Quality Control and Further Processing of Cereals and Oils,Nanjing University of Finance Economics;  
This work aims at the images with intensive corners in the target area and sparse corners in the background area. To extract the edges of target area more accurately and more completely and to eliminate the background,a target edge detection method based on SUSAN operator and corner discriminant factor is proposed. First,the corners of image are extracted by SUSAN operator and the isolated noise points in the image are filtered. Then,target corner discriminant factor is defined for elimination of corners in the background area and preservation of corners in the target area. Finally,according to the similar standard of effectiveness,other edge points are detected based on the targetcorner standard and the target edges are obtained. A large number of experimental results show that,compared with Canny method,the improved bee colony method,and the improved non-subsampled contourlet modulus maxima method,the proposed method avoids the interference of background area effectively and locate the target area accurately. The obtained edge profile can be connected and is complete with abundant details. It has better subjective visual effect and stronger anti-noise ability with less running time.
【Fund】: 国家自然科学基金(60872065);; 制造与自动化省高校重点实验室开放课题(2014);; 高速铁路线路工程教育部重点实验室开放基金(2014-HRE-01);; 江苏省粮油品质控制及深加工技术重点实验室开放基金(LYPK201304);; 江苏高校优势学科建设工程项目(2012)资助
【CateGory Index】: TP391.41
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