计算机工程

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基于Gabor 和纹理抑制的手机配件划痕检测

宋 迪,张东波,刘 霞   

  1. (湘潭大学信息工程学院,湖南湘潭411105)
  • 收稿日期:2013-09-09 出版日期:2014-09-15 发布日期:2014-09-12
  • 作者简介:宋 迪(1987 - ),男,硕士研究生,主研方向:模式识别,图像处理;张东波,教授、博士;刘 霞,硕士研究生。
  • 基金项目:

    国家自然科学基金资助项目(60835004);湖南省教育厅基金资助项目(10B109);湖南省重点学科建设基金资助项目。

Scratch Detection for Mobile Phone Accessories Based on Gabor and Texture Suppression

SONG Di,ZHANG Dong-bo,LIU Xia   

  1. (College of Information Engineering,Xiangtan University,Xiangtan 411105,China)
  • Received:2013-09-09 Online:2014-09-15 Published:2014-09-12

摘要:

经典的划痕检测方法通常采用各种边缘检测算子来完成,由于对纹理和噪声十分敏感,因此常造成大量的误判。在具有复杂纹理的金属表面检测中,误判现象尤其严重。为此,利用Gabor 滤波的条形模式检测原理,同时结合各向异性纹理抑制和滞后多阈值处理技术,提出一种用于手机配件金属表面划痕的检测方法。对金属表面图像进行Gabor 滤波,提取出划痕的骨架结构,利用各向异性纹理抑制方法抑制金属表面的纹理,再用滞后多阈值准确提取划痕。实验结果表明,该方法能极大程度地抑制非划痕区域的金属纹理,同时完整地提取出细微的划痕图像,其误检率、漏检率和轮廓检测缺失概率分别为2% ,3. 7% 和5. 5% ,明显优于基于边缘算子的划痕检测方法。

关键词: 划痕检测, Gabor 滤波, 纹理抑制, 高斯函数, 各向异性, 滞后多阈值

Abstract:

Classic scratch detection usually uses variety edge operators. Because the edge detection alogorithms are sensitive to texture and noise,they often cause a lot of false positive results. In the case of the detection of metal surfaces, due to complex textures present in the surface of metal material,the false positive results are particularly serious. Here, based on bar pattern detection principle of Gabor filtering and combining with anisotropic texture suppression and hysteresis multi-threshold technology,a scratch detection method used for mobile phone accessories is proposed. First,the method extracts the scratches frame using Gabor filtering,and secondly,uses anisotropic texture suppression on the metal surfaces. Finally,it extracts scratches accurately with hysteresis multi-threshold technology. Experimental results show that the method can greatly suppress the texture of mental surface in background. At the same time,it extracts the complete scratch images. The false positive detection rate,false negative rate and probability of contour missing achieve 2% ,3. 7% and 5. 5% respectively,and the performance of the method is obviously superior to edge-based scratch detection methods.

Key words: scratch detection, Gabor filtering, texture suppression, Gaussian function, anisotropy, hysteresis multithreshold

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