PROBABILISTIC HOUGH TRANSFORM FOR LINE DETECTION UTILIZING SURROUND SUPPRESSION

摘要：

A new probabilistic Hough transform algorithm for line detection was proposed. Instead of treating edge pixels in a binary edge image equally, a weight is bestowed to each edge pixel according to the surround suppression strength at the pixel, which can be used in either sampling stage or voting stage or both of the probabilistic Hough transform. This weight is used to put emphasis on those edge points located on clear boundaries between different objects, leading to higher probability of sampling from perceptually reasonable real lines in the edge image, as well as suppressed false peaks in Hough space formed by large amount of noise edges. Experiments on a real-world image base show that the new method gives higher line detection rate and accuracy, at the expense of moderate execution time acceptable for a broad range of applications, where the novel algorithm is preferable than other Hough transform methods tested.

关键词： Hough transform Probabilistic Hough transform Line detection Surround suppression

作者: SI-YU GUO YA-GUANG KONG QIU TANG FAN ZHANG

作者单位: College of Electrics and Information Engineering, Hunan University, Changsha 410082 China School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China Hangzhou Municipal Power Bureau, Hangzhou 310009, China

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 2993-2998

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）