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《Journal of Data Acquisition & Processing》 2005-01
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Polygonal Approximation of Digitized Curves Based on Uniqueness Wavelet Descriptor

ZHOU Zheng-dong, ZHANG Pin-zheng, SHU Hua-zhong ZHOU Wei-ping, LI Song-yi, YU Wen-xue (Department of Bimedical Engineering, Southeast University, Nanjing 210096, China)  
A new polygonal approximation method based on the uniqueness wavelet descriptor (UWD) is studied. Firstly, the 1-D periodic signal function of the polygon is obtained, then the differences are calculated between the UWD of the initial contour and those of the approximated polygons with one less vertice, the one with minimum difference is chosen as the appro-ximated polygon, thus a sequence of polygons with different number of vertices is output. By applying the procedure to some digital curves promising results are obtained. Compared with the known methods, such as area based method and Legendre moment based method, experimental results demonstrate that the UWD based algorithm gives better results.
【CateGory Index】: TP391.4
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【Citations】
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1 LI Song Yi ZHOU Jin Dan ZHANG Hui LUO Li Min (Department of Biology and Medical Engineering, Southeast University, Nanjing 210096);Moment-Based Methods for Polygonal Approximation of Digitized Curves[J];Chinese Journal of Computers;2001-04
【Co-citations】
Chinese Journal Full-text Database 5 Hits
1 YANG Guo-liang1,2,GUO Xin-yu1,ZHANG Guang-nian2,GE Qing-ping2(1 National Engineering Research Center for Information Technology in Agricultur e,Beijing 100089,China;2 Capital Normal University,Information Engineering College,Beijing 100037,Chi na) Abtract:This article introduced the development of computer vision application i n root morphological structure research domestic and overseas at first,then con cluded the main technologies such as image segmentation,thinning,vectorization which were needed in the research of root configuration.It provided a frame wo rk for same kind research in future.;Summarization of computer vision application in the research of root morphological structure[J];Agriculture Network Information;2005-11
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