Study on Defection Segmentation for Steel Surface Image Based on Image Edge Detection and Fisher Discriminant

摘要：

A hybrid image segmentation method based on edge detection and Fisher discriminant is presented to detect defection, because signal-to-noise ratio of steel surface image is very low, and defection targets are small and their shape is irregular. Firstly, gradient operator detects the edge of defection image and gradient image is gotten, then grayscale of gradient image is stretched in order to enhance image contrast. Secondly, Fisher discriminant is adopted in order to find optimum threshold, meanwhile defection targets are segmented. Lastly,noise is filtered by morphology method. Defection is auto-segmented and located by this segmentation method. Experiment results show this method can detect week defection and real-time detect defection online.

作者: J H Guo X D Meng M D Xiong

作者单位: College of Computer Science & Technology, Dalian Maritime University, Dalian 116026, China Graduate School of Chinese Academy of Sciences, Beijing 100039, China;Changchun Institute of Optics,

会议类型: 国际会议

会议名称: 第四届仪器科学与技术国际会议( 4th International Symposium on Instrumentation and Science and Tcchnology)

会议地点: 哈尔滨

会议语种:英文

页码: 364-368

在线出版日期: 2006-08-08（万方平台首次上网日期，不代表论文的发表时间）