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A segment detection method based on improved Hough transform (EI CONFERENCE)

文献类型：会议论文

作者Yao Z.-J.
出版日期2006
会议名称ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005
会议地点Changchun, China
关键词Hough transform is recognized as a powerful tool in shape analysis which gives good results even in the presence of noise and the disconnection of edge. However 3. applying the standard Hough transform equation to every point of the input image edge 4. according to the local threshold 6. merging the segments whose extreme points are near. Experiment results show the approach not only can recognize regular geometric object but also can extract the segment feature of real targets in complex environment. So the proposed method can be used in the target detection of complicated scenes traditional Hough transform can only detect the lines 2. quantizing the parameter space and extracting a group of maximums according to the global threshold eliminating spurious peaks which are caused by the spreading effects and will improve the precision of tracking. cannot give the endpoints and length of the line segments and it is vulnerable to the quantization errors. Based on the analysis of its limitations Hough transform has been improved in order to detect line segment feature of targets. The algorithm aims to avoid the loss of spatial information as well as to eliminate the spurious peaks and fix on the line segments endpoints accurately 5. fixing on the endpoints of the segments according to the dynamic clustering rule which can expediently be used for the description and classification of regular objects. The method consists of 6 steps: 1. setting up the image parameter and line-segment spaces
收录类别EI
源URL[http://ir.ciomp.ac.cn/handle/181722/33666]  
专题长春光学精密机械与物理研究所_中科院长春光机所知识产出_会议论文
推荐引用方式
GB/T 7714		 Yao Z.-J.. A segment detection method based on improved Hough transform (EI CONFERENCE)[C]. 见:ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005. Changchun, China.

入库方式： OAI收割

来源：长春光学精密机械与物理研究所

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