光电工程, 2012, 39 (5): 45, 网络出版: 2012-05-31   

基于目标轮廓的附着物定位与剔除方法

A Method of Location and Elimination of Foreign Matters Based on Navigation Contour
作者单位
天津大学精密测试技术及仪器国家重点实验室,天津 300072
摘要
工业现场清洁过的微型工件表面仍会有少量灰尘、发屑等附着物存在,在微型工件的视觉检测系统中会因其改变提取的目标轮廓而影响检测结果。为此,以灰尘与工件存在较小差异的任意位置和形状的一类附着物为考察对象,以区域生长提取的目标轮廓为先验背景,研究附着物定位与剔除算法。首先,获取沾染附着物的工件图像,采用基于区域的分割算法做处理,以建立工件轮廓的先验知识;其次,从曲率角度定位附着物轮廓角点,以此剔除附着物轮廓;最后,根据先验知识自动修复断开的外轮廓。实验结果显示,加入附着物去除与修复算法后测量精度没有降低,测量结果误差 6 μm 以内,图像边缘的定位准确度能够给予保证。表明所研究的附着物定位与剔除方法使检测系统在允许微小附着物存在并且不影响测量精度的情况下,实现了目标轮廓的正确判别,提高了视觉检测系统的可靠性。
Abstract
Detection results can be affected by foreign matters such as dust and scurf since they lead to the contour of workpieces changed in vision detection system,even mini-parts have cleaned yet. Therefore, a study of location and elimination of foreign matters algorithm is presented based on priori knowledge of target contour extracted by region growing. The algorithm, no matter their positions and shapes, especially suits for foreign matters which have an obviously gray level compared to objects. Firstly, a work-piece image with foreign matters was obtained. A segmentation algorithm based on region was employed for priori knowledge on contour. Then, in order to eliminate an outer contour of a foreign matter, the corner of this contour were located from the curvature point of view. Finally, the disconnected outer contour was intelligently repaired according to the built priori knowledge. Experimental results indicate that the measurementaccuracy does not reduce and the error of measuring result is within 6 μm. No matter if there are foreign matters on the surface of parts, this method can still obtain the right judgments. Additionally, it also can guarantee the accuracy of measurement unchanged, so as to improve the reliability of the whole vision detecting system.
参考文献

[1] 李国辉,苏真伟,夏心怡 . 基于不规则成像机器视觉的棉花白色异纤检测算法 [J].农业机械学报, 2010, 41(5):164-167. LI Guo-hui,SU Zhen-wei,XIA Xin-yi. Algorithm for inspection of white foreign fibers in cotton by machine vision with irregular imaging function [J]. Transactions of the Chinese Society for Agricultural Machinery,2010,41(5): 164-167.

[2] ZHANG F,BRESEE R. Fabric defect detection and classification using image analysis [J]. Textile Research Journal (S0040-5175),1995,65(1):1–9.

[3] CHETVERIKOV D,HANBURY A. Finding defects in texture using regularity and local orientation [J]. Pattern Recognition(S0031-3203),2002,35:203–218.

[4] SEZER O G,ERCIL A,ERTUZUN A. Using perceptual relation of regularity and anisotropy in the texture with independent components for defect detection [J]. IEEE Pattern Recognition(S0031-3203),2007,40(1):121–133.

[5] RUSEN Meylani. 2-D Iteratively reweighted least squares lattice algorithm and its application to defect detection in textured images [J]. Transactions on Fundamentals of Electronics,Communications and Computer Sciences (S0916-8508),2006,89(A5):1484–1494.

[6] 朱铮涛,郑国盾 . 颗粒粮食中异物的视觉检测算法与实现 [J].农业科学与技术:英文版, 2009,10(5):42-44. ZHU Zheng-tao,ZHENG Guo-dun. Visual identification method and implementation of impurities in food grain [J]. Agricultural Science &Technology,2009,10(5):42-44.

[7] 陈杰,李志敏,钟先信,等 . 烟草在线检测与异物剔除系统 [J].光电工程, 2003,30(5):51-54. CHEN Jie,LI Zhi-min,ZHONG Xian-xin,et al. Tobacco on-line Detection and Foreign Matter Eliminating System [J]. Opto-Electronic Engineering,2003,30(5):51-54.

[8] 姚富光,钟先信,唐向阳 . 异物在线识别中一类支持向量机机理及实现 [J].光学精密工程, 2009,17(4): 937-942. YAO Fu-guang,ZHONG Xian-xin,TANG Xiang-yang. Mechanism and implementation of one class support vector machines in fast foreign real-time recognition [J]. Optics and Precision Engineering,2009,17(4):937-942.

[9] Luc Vincent,Pierre Soille. Watersheds in Digital Spaces:An Efficient Algorithm Based on Immersion Simulations [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence (S0162-8828),1991,13(6):583-595.

[10] NAJMAN Laurent,SCHMITT Michel. Geodesic Saliency of Watershed Contours and Hierarchical Segmentation [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence (S0162-8828),1996,12(18):1163-1173.

[11] WANG W X. Binary Image Segmentation of Aggregates based on Polygonal Approximation and Classification of Concavities [J]. Pattern Recognition(S0031-3203),1998,31(10):1503-1524.

[12] 董文明,吴乐华,姜德雷 . 基于分形特征参数的目标边缘检测算法 [J].光电工程, 2009,36(6):21-25. DONG Wen-ming, WU Le-hua, JIANG De-lei. Edge Detection Algorithm Based on Fractal Features [J]. Opto-Electronic Engineering,2009,36(6):21-25.

[13] 陶冰洁,魏宇星 . 采用多源图像分形特征的多目标检测方法 [J].光电工程, 2009,36(12):11-15. TAO Bing-jie,WEI Yu-xing. Multi-target Detection Using Fractal Feature Fusion Of Different Source Image [J]. Opto-Electronic Engineering,2009,36(12):11-15.

[14] 丁天怀,郏东耀 . 利用多颜色空间特征融合方法检测近似目标 [J].清华大学学报:自然科学版, 2006,46(2): 176-179. DING Tian-huai,JIA Dong-yao. Detection of similar targets using multiple color space feature fusion [J]. Journal of Tsinghua University:Science and Technology,2006,46(2):176-179.

[15] SHOTTON J D J. Contour and Texture for Visual Recognition of Object Categories [D]. Queens’College,University of Cambridge,2007.

[16] ADAMS R,BISCHOF L. Seeded Region Growing [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence(S0162-8828),1994,16(6):641-647.

[17] 赵渊博,赵慧洁 . 挠性接头薄筋在线测量图像分割方法研究 [J].光学精密工程, 2005,13(增 1):153-157. ZHAO Yuan-bo,ZHAO Hui-jie. Study on image segmentation method for on-line measurement of tendon thickness for flexible connector [J]. Optics and Precision Engineering,2005,13(s1):153-157.

[18] YU Xiao-han,JUHA Yla-Jailski,Huttunen O,et al. Image Segmentation Combining Region Growing and Edge Detection

    [C] // 11th IAPR International Conference on Pattern Recognition,The Hague,Netherlands,August 30- Sept 3, 1992,III:481-484.

栗琳, 王仲, 蔡振兴, 王向军. 基于目标轮廓的附着物定位与剔除方法[J]. 光电工程, 2012, 39(5): 45. LI Lin, WANG Zhong, CAI Zhen-xing, WANG Xiang-jun. A Method of Location and Elimination of Foreign Matters Based on Navigation Contour[J]. Opto-Electronic Engineering, 2012, 39(5): 45.

本文已被 1 篇论文引用
被引统计数据来源于中国光学期刊网
引用该论文: TXT   |   EndNote

相关论文

加载中...

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!