基于机器视觉的首饰识别  

Jewelry Recognition Based on Machine Vision

作　　者：郑李强 赵飞[1] 郭江涛 ZHENG Li-qiang;ZHAO Fei;GUO Jiang-tao(School of Mechanical Engineering & Automation,Northeastern University,Shenyang,Liaoning 110819,China)

机构地区：[1]东北大学机械工程与自动化学院

出　　处：《计算技术与自动化》2019年第3期103-106,共4页Computing Technology and Automation

摘　　要：为了实现首饰的自动识别,设计了一套基于机器视觉的首饰识别系统,并提出相应的算法。采用8种首饰作为试验样本,利用G+R分量和的颜色阈值分割法,并用27×27的模板对二值化图像进行滤波,采用2×2窗口内像素灰度值之和并结合阈值的边缘提取方法。提取面积特征和图像形心到边缘的距离特征。对面积判断其大小在设定数值范围内,对距离特征采用互相关算法处理。实验结果表明,该方法的识别准确率达100%,识别一个首饰所用时间约3秒,满足在实际中应用的要求。In order to realize automatic recognition of the jewelry,a set of jewelry recognition system based on machine vision is designed,and the corresponding algorithm is proposed.In this study,8 different kinds of jewels are used as experimental samples.The color threshold segmentation method is used by the componentsofG+R.Binary image is filtered with a template of 27×27 pixel.A method of edge extraction is proposedbased on values of pixels combined with the threshold by the 2×2pixel window.The features of areaand the distancefrom image centroid to edgeare extracted.The values of area are judgedwithin the limits of given values,and the cross-correlation algorithm is applied to the values of distance feature.The experimental results show that the precision rate of the method is 100% and average recognition time for each is about 3 seconds,which meets the requirements of practical application.

关 键 词：机器视觉 首饰 特征提取 识别 互相关算法 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]