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浙江大学学报（理学版）
浙江大学学报（理学版）  2019, Vol. 46 Issue (3): 288-294    DOI: 10.3785/j.issn.1008-9497.2019.03.004
文化计算     
融合形态学连通域和CV模型的民族服饰图案纹样元素分割方法
侯小刚1, 陈洪2, 赵海英2
1.北京邮电大学 网络技术研究院，北京 100876
2.北京邮电大学 计算机学院，北京 100876
The national costume pattern elements segmentation by incorporating morphology connected component and CV model
Xiaogang HOU1, Hong CHEN2, Haiying ZHAO2
1.Institute of Network Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China
2.School of Computer Science, Beijing University of Posts and Telecommunications, Beijing 100876, China
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摘要： 对民族服饰图案进行自动分割以提取图案纹样元素，是民族服饰图案素材库构建急需解决的难题。通过融合形态学连通域标记和CV模型（MCC-CV），提出了一种民族服饰图案自动分割方法，首先对民族服饰图案进行预处理，然后采用形态学连通域标记算法获得待分割目标的位置和大致轮廓信息，对CV模型进行初始化，最后通过CV模型对不同分割目标进行边缘追踪，以实现民族服饰图案纹样元素的自动分割。实验表明，融合形态学连通域和CV模型的民族服饰图案纹样元素自动分割方法在边界召回率（BR）为0.5时，分割准确率为60%，与其他自动分割算法相比，该算法更为有效，满足了民族服饰图案素材库建设对图案纹样元素分割的基本要求。
关键词： 民族服饰;  图案纹样元素;  形态学连通域和CV模型（MCC-CV）;  自动分割    
Abstract: A automatic segmentation of national costume patterns to extract the pattern elements is an urgent problem to be solved in the construction of the national costume pattern material library. In this paper, we propose an automatic segmentation method by incorporating morphology connected component labeling and CV model (MCC-CV). Firstly, we carry out the image preprocessing on national dress patterns. Then，the location of the target pattern is obtained by using the morphology connected component labeling ,which serves as the initial contour of the CV model. Finally, the automatic segmentation of national costume pattern elements is realized by detecting the edge of the pattern gene using the CV model. Experimental results show that the accuracy of MCC-CV model is 60% under the premise boundary recall 0.5, which satisfies the basic requirements for the national costume pattern material library construction.
Key words: national costume    pattern elements    morphology connected component and CV model (CCL-CV)    automatic image segmentation
收稿日期: 2019-02-20 出版日期: 2019-05-25
CLC:  TP391. 4  
基金资助: 北京市科技计划项目(D171100003717003)；北京市科技重大专项(Z171100004417032).
通讯作者: ORCID: http://orcid.org/0000-0002-0240-4573 ，E-mail：zhaohaiying@bupt.edu.cn.     E-mail: zhaohaiying@bupt.edu.cn.
作者简介: 侯小刚(1984—)，ORCID: http://orcid.org/0000-0001-6912-873X，男，博士研究生，主要从事数字图像处理等相关研究.
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引用本文:

侯小刚, 陈洪, 赵海英. 融合形态学连通域和CV模型的民族服饰图案纹样元素分割方法[J]. 浙江大学学报（理学版）, 2019, 46(3): 288-294.

Xiaogang HOU, Hong CHEN, Haiying ZHAO. The national costume pattern elements segmentation by incorporating morphology connected component and CV model. Journal of Zhejiang University (Science Edition), 2019, 46(3): 288-294.

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https://www.zjujournals.com/sci/CN/10.3785/j.issn.1008-9497.2019.03.004    或    https://www.zjujournals.com/sci/CN/Y2019/V46/I3/288

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