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Hough变换空间中基于直线的模板匹配 被引量:3

Template Matching Based on Straight Lines in Hough Transform Space
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摘要 现有算法精度低,且线段被完全遮挡时会出现误匹配甚至无法匹配等情况,为此提出改进的直线匹配算法。该算法在θ?匹配阶段改进搜索方法,通过删除缺失目标直线对应的模板图像直线,建立新的模板图像轮廓再进行匹配,解决直线段缺失时无法匹配问题;在ρ?匹配阶段引入RANSAC算法剔除误匹配直线对,解决误匹配问题。实验表明,该方法能解决目标直线被遮挡问题,并提高匹配精度。 As to the previous algorithms,the accuracy of matching is low and when the line segments are occupied,the matching is failure or even not to be implemented.Focusing on these instances,this paper presents a modified method.In matching,a new search method establishes a new contour of the model image via removing its lines corresponding to the missing lines,so it solves the problem that the procedure of matching can not be implemented when several line segments in model image are absence;and in matching,the Random Sample Consensus(RANSAC) algorithm is introduced to settle the problem of mismatch by removing the pairs of mismatching lines.Experiments demonstrate that the proposed algorithm can settle the problem brought by occupied lines,and promote the accuracy of the matching.
出处 《计算机工程》 CAS CSCD 北大核心 2011年第10期140-142,共3页 Computer Engineering
基金 国家自然科学基金资助项目(60672135)
关键词 HOUGH变换 目标检测 RANSAC算法 SOBEL算子 最小二乘 Hough transform object detection Random Sample Consensus(RANSAC) algorithm sobel operation least squares
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参考文献5

  • 1Homberg A.Handbook of Machine Vision[M].[S.l.] :WileyVCH,2006.
  • 2张小军,胡福乔.基于广义霍夫变换的芯片检测[J].计算机工程,2009,35(23):252-254. 被引量:9
  • 3Ballard D H.Generalizing the Hough Transform to Detect Arbitrary Shapes[J].Pattern Recognition,1981,13(2):111-122.
  • 4Okuzonp T,Wakizako H.Object Detection Using Straight Line Matching in θ-ρ Space[J].Electronics and Communications in Japan,2010,93(3):34-41.
  • 5Wei Zhan,Kosecka J.Generalized RANSAC Framework for Relaxed Correspondence Problems[C] //Proc.of International Symposium on 3D Data Processing,Visualization and Transmission.Fairfax,USA:[s.n.] ,2006.

二级参考文献4

  • 1Ballard D H. Generalizing the Hough Transform to Detect Arbitrary Shapes [J]. Pattern Recognition, 1981, 13(2): 111-122.
  • 2Ma De, Chen Xing. Hough Transform Using Slope and Curvature as Local Properties to Detect Arbitrary 2D Shapes[C]//Proc. of the 9th lnt'l Conf. on Pattern Recognition. Beijing, China: [s. n.], 1988: 511-513.
  • 3Ser P K, Siu W C. Non-analytic Object Recognition Using the Hough Transform with the Matching Technique[J]. Computers and Digital Techniques. 1994, 141(1): 11-16.
  • 4Thomas A D H. Compressing the Parameter Space of the Generalized Hough Transform[J]. Pattern Recognition Letters, 1993, 13(2): 107-112.

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