纺织学报 ›› 2010, Vol. 31 ›› Issue (2): 125-128.

• 管理与信息化 • 上一篇    下一篇

基于贝叶斯决策及半监督聚类的织物图像分割

包晓敏;彭霄;汪亚明;曹作宝   

  • 收稿日期:2009-02-19 修回日期:2009-09-18 出版日期:2010-02-15 发布日期:2010-02-15

Textile image segmentation based on semi-supervised clustering and Bayes decision

BAO Xiao-min;PENG Xiao;WANG Ya-ming;CAO Zuo-bao   

  • Received:2009-02-19 Revised:2009-09-18 Online:2010-02-15 Published:2010-02-15

摘要:

为提高纺织CAD技术,依据半监督聚类理论,提出一种以最小错误率贝叶斯决策为准则的半监督聚类的织物图像分割算法。这种算法利用有限的人工信息,即在织物图像上点击有限的几个点以标识相应区域之间的关系,从而得到满足用户给定限制的织物图像分割结果。用该算法首先对织物图像进行量化转换处理,而后在贝叶斯模式识别中集成先验的分割信息进行色彩聚类。实验结果表明,该算法用于织物图像分割是可行的。

Abstract:

To improve the technology of the textile CAD, we proposed a new way of textile image segmentation by the minimum error Bayes decision theory based on the semi-supervised clustering. The algorithm makes use of limited human assistance, i.e. indicating the relationship of some different regions by clicking some limited points on the textile image using a mouse, to get the final accurate results of segmentation which satisfies the requirement of customers. The algorithm quantizes the textile image. Then it clusters colors in Bayes decision with prior segmentation information. The results demonstrated that this algorithm is a feasible way for textile image segmentation.

中图分类号: 

  • TP391.41
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