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[1]孙麒. 基于极大似然估计的织物图像分割[J].浙江理工大学学报,2013,30(01):12-15.
　SUN Qi. Textile Image Segmentation Based on theMaximum Likelihood Algorithm[J].Journal of Zhejiang Sci-Tech University,2013,30(01):12-15.
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 基于极大似然估计的织物图像分割()
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浙江理工大学学报[ISSN:1673-3851/CN:33-1338/TS]

卷:
第30卷
期数:
2013年01期
页码:
12-15
栏目:
(自科)纺织与服装工程
出版日期:
2013-01-20

文章信息/Info

Title:
 Textile Image Segmentation Based on theMaximum Likelihood Algorithm
文章编号:
16733851 (2013) 01001204
作者:
 孙麒
 浙江理工大学信息学院, 杭州 310018
Author(s):
 SUN Qi
 School of Informatics, Zhejiang SciTech University, Hangzhou 310018, China
关键词:
 ; 图像分割;  边缘检测;  线段检测;  极大似然估计
分类号:
TP391.4
文献标志码:
A
摘要:
    为了实现利用机器视觉技术进行织物图像检测,对织物图像的分割进行了研究。提出一种基于从图像中检测直线段或者曲线段的边缘检测方法,基本思路是利用极大似然法评估出边缘像素点的边缘切线方向,然后逐点连接切线倾角变化微小的相邻边缘像素得到线段。由于在相邻像素间移动模板时,只有模板边缘行列的像素对新的评估产生影响,进一步给出了加速策略。实验结果表明,针对有较好对比度的灰度织物图像,该方法在图像分割中是一种实用的方法。

参考文献/References:

［1］ 诸葛振荣, 徐敏, 刘阳飞. 基于MeanShift的织物图像分割算法［J］. 纺织学报, 2007, 28(10): 108111.
［2］ 李鹏飞, 张宏伟. 基于Kmeans 聚类的纺织品印花图案区域分割［J］. 西安工程大学学报, 2008, 22(5): 551554.
［3］ Kenneth R Castleman. 数字图像处理［M］. 朱志刚, 林学訚, 石定机, 等译. 北京: 电子工业出版社, 2004.
［4］ Bouthemy P. A maximumlikelihood framework for determining moving edges［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1989, 11(5): 499–511.
［5］ Kahn P. Local determination of a moving contrast edge［J］. IEEE Transactions on Pattem Analysis and Machine Intelligence, 1985, 7(4): 402409.
［6］ BOVIK A C. Handbook of Image and Video Processing［M］. 2nd. New York: Academic Press, 2005.
［7］ Canny J. A computational approach to edge detection［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1986, 8(16): 679698.
［8］ Freeman H. On the encoding of arbitrary geometric configurations［J］. IRE Trans Electronics and Computers, 1961, 10(2): 260268.

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备注/Memo

备注/Memo:
收稿日期： 2012-09-30
基金项目： 浙江省教育厅资助项目(Y200909797)
作者简介： 孙麒(1977-)，女，浙江诸暨人，副教授，主要从事模式识别与图像处理方向的研究。
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