北京科技大学学报Issue(5)：688-694,7.DOI:10.13374/j.issn1001-053x.2014.05.018
基于马氏距离和模糊C均值聚类的抠图算法与应用
Matting algorithm and application based on Mahalanobis distance and the fuzzy C-means clustering algorithm
摘要
Abstract
ABSTRACT Based on Mahalanobis distance and the fuzzy C-means algorithm, this article introduces a digital color image matting algorithm. First the red, green and blue color components of color image pixels are normalized. Second the appropriate mask as a sample set is selected in the background of the normalized image, and the Mahalanobis distance between each pixel and the sample set is calculated. Third the calculated Mahalanobis distances are classified into two categories using the fuzzy C-means clustering algorithm:the foreground and the background. Finally, the quality of the matting is improved using the filling-hole technique. Eight images have been processed for comparison, the results show that this algorithm can automatically segment these images, and is better than the Mahalanobis distance algorithm, fuzzy C-means clustering algorithm and linear regression algorithm.关键词
图像抠图/马氏距离/模糊C均值聚类/填洞Key words
image matting/Mahalanobis distance/fuzzy C-means clustering algorithm/filling-holes分类
信息技术与安全科学引用本文复制引用
张敏,闵乐泉,张群,刘飒..基于马氏距离和模糊C均值聚类的抠图算法与应用[J].北京科技大学学报,2014,(5):688-694,7.基金项目
国家自然科学基金资助项目(61074192) （61074192）
北京市教育委员会科学研究基金资助项目(KM201110020013) （KM201110020013）
