基于机器视觉的多铆钉自动检测算法研究  

Research of automatic detection algorithm for multi-rivets based on machine vision

作　　者：郭全民[1] 胡辉[1] 

机构地区：[1]西安工业大学电子信息工程学院,陕西西安710032

出　　处：《传感器与微系统》2013年第4期48-50,53,共4页Transducer and Microsystem Technologies

基　　金：陕西省教育厅自然专项科研计划资助项目(09JK483)

摘　　要：为了克服传统人工铆钉检测工效低、精度不易控制等弊端,提出了一种基于机器视觉的多铆钉非接触式自动检测算法。采用改进的OTSU算法对采集到的铆钉图像进行分割,有效地减少了污点区域的误划分。为解决铆钉方位的随机性对检测过程造成的影响,采用最小外接矩形法定位铆钉轮廓主轴,克服了复杂工业环境中的不确定因素。通过计算铆钉轮廓各点在两侧支撑区间内曲率的方法识别轮廓特征点,有效减少了噪声在曲率计算中的权重,并提高了识别精度。实验表明:该系统检测精度高,且误检率低,能满足铆钉生产在线检测的要求。To overcome defects of traditional artificial rivets detection,such as low work efficiency and unmanageable precision,a non-contact automatic detection algorithm for multi-rivets based on machine vision is proposed.The improved OTSU algorithm is adopted to segment collected rivet image which effectively reduce erroneous segmentation of stain areas.In order to resolve the impact caused by the randomness of rivets orientation on test process,the minimum enclosing rectangle method is adopted to position the outline spindle of rivet,which conquers the uncertain factors in complex industrial environments.Identify the outline feature points by calculating curvature of each rivet contour point in the both sides of the support region,which effectively reduces weight of noise in curvature calculation and improve the recognition precision.The experiments show that the system has advantageous of high detection precision and low false detection rate,and can meet on-line detection requirements of rivets.

关 键 词：铆钉检测 机器视觉 图像分割 特征点识别 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]