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《Acta Electronica Sinica》 2017-08
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Object Detection Based On Salient Contour of Image

BI Wei;HUANG Wei-guo;ZHANG Yong-ping;GAO Guan-qi;ZHU Zhong-kui;School of Urban Rail Transportation,Soochow University;  
To address detection difficulty caused by complex scene and the deformation of the object,the salient contour of image based method is proposed in this work. Firstly,the outline of image is extracted by Globalized probability of boundary,and then the improvement of the Otsu for adaptive threshold processing is used to attain the salient contour. Next,the robust fan shape model of the object is constructed by detecting and removing the unstable contour of the object. Finally,three similar matching strategies are proposed by jointing several local and global features of contour. They are based on the features probability density distribution and can detect object,its mirror flip and rotated object,respectively. Through the experimental analysis of multiple databases,the proposed method can effectively detect object and its mirror flip,and at the same time,it can also effectively detect the rotated object in the small range of rotation angle.
【Key Words】: contour extraction fan shape model shape matching object detection
【Fund】: 国家自然科学基金(No.51405320);; 苏州自然科学基金(No.SYG201511)
【CateGory Index】: TP391.41
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