A Method to Auto-estimate Edge Detection Direction

摘要：

　　In machine vision measurement,the edge is a key point for fitting geometric parameter.There are two problems in the edge detection process.First,there is redundant information for the object with complex shape in the field of the view.Second,the surface of the object is full of texture which is misidentified as the edge.The texture processes similar feature to the edge and cannot be removed by filter.To solve the above problems,vision sight is proposed to get an interesting region and remove redundant information.A new algorithm based on fuzzy entropy is used to auto-estimate the edge detection direction from the pure region to mixed region in order to avoid the textures which misidentified as the edge.Comparing the algorithm with Canny,the former gets less texture points than the latter.A mask film is used as a standard to weight the validity of the algorithm.The experimental result shows that the algorithm proposed by this paper is robust and accuracy in detecting edge.

关键词： edge detection vision sight fuzzy entropy detection direction

作者: Z. Yin B.G. Liu F.D. Chen G.D. Liu F.Wan

作者单位: Harbin Institute of Technology, Harbin 150001, China

会议类型: 国际会议

会议名称: 2012第八届精密工程测量和仪器仪表国际研讨会(ISPEMI2012)

会议地点: 成都

会议语种:英文

页码: 1-8

在线出版日期: 2012-08-08（万方平台首次上网日期，不代表论文的发表时间）