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基于主元分析和聚类的直线检测算法

Approach for line detection based on principal component analysis and clustering

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【作者】 刘巍金文标肖仙谦

【Author】 LIU Wei1,JIN Wen-biao1,2,XIAO Xian-qian2(1.College of Computer Science and Technology,Chongqing University of Posts and Telecommunications,Chongqing 400065,China;2.College of Science,Hangzhou Dianzi University,Hangzhou Zhejiang 310018,China)

【机构】 重庆邮电大学计算机科学与技术学院杭州电子科技大学理学院

【摘要】 针对现有的直线检测算法中,基于霍夫变换类算法开销大且易产生虚假结果,基于链码跟踪类方法鲁棒性和适应性较差的问题,提出一种新的直线检测算法。对边缘图像做分块链码跟踪产生链码串,然后对链码串做主元分析(PCA)构造线段,最后采用聚类方法合并线段以产生直线。实验结果表明,该算法速度较快,检测结果较理想,且对较复杂、细节丰富的图像也具有良好的检测结果。

【Abstract】 In the existing line detection methods,those based on Hough Transformation(HT) have a huge cost and always bring false results,and others based on chain tracing are weak on robustness and adaptability.This paper proposed a new approach for line detection,in which,the chain was generated by chain tracing in edge image block by block,then the Principal Component Analysis(PCA) was used on the chain to construct segments,at last the lines were got by merging the segments through clustering.The experimental results show the approach is fast and gives good results,and especially it performs well in highly complex and detail rich images.

【基金】 杭州电子科技大学科研项目科研启动基金资助项目(KYS075609066)
  • 【文献出处】 计算机应用 ,Journal of Computer Applications , 编辑部邮箱 ,2011年05期
  • 【分类号】TP391.41
  • 【被引频次】13
  • 【下载频次】323
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