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基于减法聚类的网格霍夫变换

  

  • 出版日期:2016-06-30 发布日期:2016-06-28
  • 基金资助:
    :“十二五”国家科技支撑计划(2013BAH18F02, 2013BAH72B01);玉林师范学院重点科研项目(2011YJZD16)

A Gridding Hough Transform Based on Subtractive Clustering

  • Online:2016-06-30 Published:2016-06-28

摘要: 为了解决网格霍夫变换因人工设置投票参数不当造成的直线漏检和形成伪直线的问题,提出一种基于减法聚类的无投票参数的网格霍夫变换。首先采用两阶段单调扫描方法提取尽量长的直线单元,然后利用直线单元在数量上长的少、短的多的特点自动确定参与投票的直线单元集合,最后利用减法聚类实现直线单元的容错投票。实验结果表明该算法不但执行速度快,而且无需人工设置投票参数,配合减法聚类的容错投票,较好地避免了因人工设置投票参数不当造成的直线漏检和形成伪直线的问题。

关键词: 减法聚类, 直线检测, 霍夫变换, 网格化

Abstract: To solve the problem of undetected-line and pseudo-line resulting from unsuitable manual voting parameter in gridding Hough transform, a non-voting-parameter gridding Hough ttansform based on subtractive clustering is proposed. Firstly a two-stage scan in monotonous way is adopted to make every linelet as long as possible, and then the subset of voting linelets is automatically determined by characteristics of the lack of long linelets and the abundance of short linelets. Finally a fault-tolerant voting process is realized by using subtractive clustering. Our experimental results show that the proposed algorithm has a fast execution speed, and without manual voting parameter, and is very good to avoid the problem of undetected-line and pseudo-line resulting from unsuitable manual voting parameter by combining it with subtractive clustering.

Key words: subtractive clustering, straight-line detection, Hough transform, gridding