Integrated color defect detection method for polysilicon wafers using machine vision

作     者：Zai-Fang Zhang Yuan Liu Xiao-Song Wu Shu-Lin Kan 

作者机构：School of Mechatronic and Automation EngineeringShanghai University School of Mechanical and Power EngineeringShanghai JiaoTong University 

出 版 物：《Advances in Manufacturing》 (先进制造进展（英文版）)

年 卷 期：2014年第2卷第4期

页      面：318-326页

核心收录：

学科分类：0817[工学-化学工程与技术] 08[工学] 0807[工学-动力工程及工程热物理] 080203[工学-机械设计及理论] 0805[工学-材料科学与工程（可授工学、理学学位）] 0802[工学-机械工程] 0811[工学-控制科学与工程] 0801[工学-力学（可授工学、理学学位）] 

基　　金：supported by the National Natural Science Foundation of China(Grant Nos.51205242,and 51075261) the Shanghai Science and Technology Innovation Action Plan,China(Grant No.13111102900) 

主　　题：Polysilicon wafers Color defect detection Machine vision Fuzzy color clustering Region growingmethod 

摘      要：For the typical color detects of polysilicon wafers, i.e., edge discoloration, color inaccuracy and color non-uniformity, a new integrated machine vision detection method is proposed based on an HSV color model. By transforming RGB image into three-channel HSV images, the HSV model can efficiently reduce the disturbances of complex wafer textures. A fuzzy color clustering method is used to detect edge discoloration by defining membership function for each channel image. The mean-value classi- fying method and region growing method are used to identify the other two defects, respectively. A vision detection system is developed and applied in the produc- tion of polysilicon wafers.