Computer Engineering and Applications ›› 2012, Vol. 48 ›› Issue (32): 224-228.

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Research on segmentation method for silicon steel surface defect based on structure tensor and active contour

SONG Kechen1, YAN Yunhui1, WANG Zhan1, HU Changfa2   

  1. 1.School of Mechanical Engineering & Automation, Northeastern University, Shenyang 110819, China
    2.CSR Zhuzhou Electric Locomotive Institute CO., LTD, Zhuzhou, Hunan 412001, China
  • Online:2012-11-11 Published:2012-11-20

融入结构张量和活动轮廓的硅钢表面缺陷分割

宋克臣1,颜云辉1,王  展1,胡昌发2   

  1. 1.东北大学 机械工程与自动化学院,沈阳 110819
    2.南车株洲电力机车研究所有限公司,湖南 株洲 412001

Abstract: In order to address the segmentation problem for cold rolled silicon steel surface defect based on the texture background, a novel method based on structure tensor and active contour model is proposed. Image local information is introduced to the structure tensor. In the extracted feature space of structure tensor, KL distance is treated as a regional similarity measure of the probability density to establish active contour model for image segmentation. The numerical solution of Split-Bregman is used to solve the model. The proposed method is introduced to segment silicon steel surface defects, which are longitudinal scratches, horizontal scratches, foreign bodies, and holes. The experimental results show that this method can segment the silicon steel surface defect areas accurately.

Key words: silicon steel, surface defect, structure tensor, active contour, image segmentation

摘要: 为了解决在纹理背景下冷轧硅钢表面缺陷的分割问题,提出了基于局部信息结构张量和活动轮廓模型的硅钢表面缺陷分割方法。将图像的局部信息引入到结构张量中;在结构张量提取的特征空间中,以KL距离作为区域的概率密度相似性度量建立分割图像的活动轮廓模型;采用Split-Bregman数值解法对模型进行求解。运用提出的分割方法对硅钢表面的一些常见缺陷如纵向划伤、横向划伤、异物和孔洞等进行分割实验。实验结果表明,该方法可以准确地分割出硅钢表面缺陷区域,验证了该方法的有效性。

关键词: 硅钢, 表面缺陷, 结构张量, 活动轮廓, 图像分割