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基于主元分析和聚类的直线检测算法

         

摘要

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.%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.

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