[1]张黔,杨润玲,刘警锋,等. 带钢表面缺陷图片的去噪和分割方法研究[J].计算机技术与发展,2015,25(04):26-29.
　ZHANG Qian,YANG Run-ling,LIU Jing-feng,et al. Research on Denoising and Segmentation Method of Steel Strip Surface Defect Images[J].,2015,25(04):26-29.
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 带钢表面缺陷图片的去噪和分割方法研究()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
25
期数:
2015年04期
页码:
26-29
栏目:
智能、算法、系统工程
出版日期:
2015-04-10

文章信息/Info

Title:
 Research on Denoising and Segmentation Method of Steel Strip Surface Defect Images
文章编号:
1673-629X（2015)04-0026-04
作者:
 张黔; 杨润玲; 刘警锋; 肖磊
 西安建筑科技大学 信息与控制工程学院
Author(s):
 ZHANG Qian; YANG Run-ling; LIU Jing-feng; XIAO Lei
关键词:
 ; 表面缺陷; 中值滤波; 双阈值滤波; 模糊聚类
Keywords:
 ; surface defects; median filtering; double threshold filtering; fuzzy clustering
分类号:
TP391.41
文献标志码:
A
摘要:
 去噪和图像分割是带钢表面检测系统的重要环节。传统的滤波方法在去噪的同时会造成图像模糊，影响缺陷检测。为了解决这个问题，结合均值滤波和中值滤波的特性，针对含有高斯噪声和脉冲噪声的带钢表面缺陷图片提出了一种新的去噪方法—双阈值滤波。该方法通过设定两个阈值分别区分噪声点和非噪声点、高频部分和低频部分，然后进行相应的处理。应用模糊聚类算法，进一步对去噪图像进行分割。实验结果表明，所提出的去噪方法简单有效，分割方法应用准确。
Abstract:
 Denoising and image segmentation is an important process of strip surface detection system. The traditional filtering methods denoise at the same time blur the image,and influence the fault detection. In order to solve this problem,combined with the characteristics of median filter and mean filter,on the steel strip surface defect images containing Gauss noise and impulse noise,a new method of de-noising named double threshold filtering is proposed,which sets two thresholds to distinguish noise and non noise,high frequency and low frequency respectively,and then carry out corresponding treatment. Apply the fuzzy clustering algorithm to further segment the denoising image. The experimental results show that the proposed denoising method is simple and effective,application of segmentation method is accurate.

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更新日期/Last Update: 2015-06-02