摘要
提出了一种直接在JPEG图像压缩域进行肤色检测的算法.该算法首先在熵解码后的DCT系数中提取图像块的颜色特征和纹理特征,然后利用数据挖掘建立用于表征压缩域图像特征和肤色检测结果之间关系的肤色模型,并利用该模型进行初步肤色检测,最后利用区域生长的方法分割出图像中的肤色区域.实验结果表明,与像素域的SPM(Skin Probability Map)肤色检测算法相比,本文方法可以获得更高的检测准确率和更快的检测速度.
A novel skin color detection method in JPEG compressed domain has been proposed.Color and texture features of the image blocks are extracted from the entropy decoded DCT coefficients firstly.Then,data mining method is applied to set up the skin color model to describe the relationship between the image block features and the skin detection results,and the initial skin image blocks are detected based on the model.The skin color regions are finally segmented using region growing method.Experimental results show that,compared with the SPM（Skin Probability Map）skin color detection algorithm in pixel domain,the proposed method can achieve higher detection accuracy and faster detection speed.
出处
《电子学报》
EI
CAS
CSCD
北大核心
2010年第3期605-610,共6页
Acta Electronica Sinica
基金
国家自然科学基金(No.60772069)
国家863高技术研究发展计划(No.2008AA01A313)
关键词
肤色检测
压缩域
数据挖掘
区域生长
skin color detection
compressed domain
data mining
region growing
