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基于小波模极大值的织物疵点检测
引用本文:赵静. 基于小波模极大值的织物疵点检测[J]. 电子测量技术, 2010, 33(10): 108-110
作者姓名:赵静
作者单位:江南大学物联网工程学院,无锡,214122
摘    要:织物疵点部分相当于图像中灰度突变的奇异信号,对比传统的边缘检测方法,小波变换在检测图像微小细节边缘时具有明显的优势,能很好地刻划突变点的奇异性。首先利用小波的多尺度特性求得织物图像局部极大值点,有效提取出织物疵点区域的边缘,然后结合形状特征求出织物疵点区域的形状特征,对常见重纬、重经、缺经、缺纬、油污、破洞织物疵点图像进行仿真实验,结果表明此方法既保留了织物疵点边缘信息,又剔除了虚假边缘,最终有效地提取出了疵点区域的形状特征。

关 键 词:小波变换  模极大值  形态学  织物疵点

Fabric defect detection based on the maxima of wavelet transform modulus
Zhao Jing. Fabric defect detection based on the maxima of wavelet transform modulus[J]. Electronic Measurement Technology, 2010, 33(10): 108-110
Authors:Zhao Jing
Affiliation:Zhao Jing(Internet of Things Engineering Institute,Jiang Nan University,Wuxi 214122)
Abstract:Fabric defect is singularity signal of the gray image,compared with the traditional test methods,wavelet transform has obvious advantages in detection of minute edge details of image,and able to describe singularity better.first,use multiscale characteristic of wavelet transform to find local modulus maxima of fabic image,effectively obtain the edge of fabric defect parts,then combine morphology to find appearances of the fabric defect,experiment on common defect images of coarse pick,coarse end,end out,mis...
Keywords:wavelet transform  maxima modulus  morphology  fabric defect  
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