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Robust algorithm for extracting skin pigment concentration
from color image |
| Xu Shu-chang1, ZHANG San-yuan2, ZHANG Yin2 |
1.Department of Information Science & Engineering, Hangzhou Normal University, Hangzhou 310036, China;
2. Department of Computer Science, Zhejiang University, Hangzhou 310027, China |
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Abstract To investigate the two most important pigments of human, melanin and hemoglobin, an image-channel-difference of optical density space based algorithm was proposed for automatically extracting melanin and hemoglobin concentration distribution map from single color image. The algorithm built mathematic model between pigment and digital image based on theoretical foundation of skin structure and its optical property. The input image firstly was divided into several sub-regions. Independent component analysis (ICA) technology was performed in every sub-region to calculate Separation Vector, which is successively verified by specified rules. All the valid Separation Vectors were then re-combined to form new vectors, from which the final separation vector with minimal deviation is selected. The pigment concentration distribution maps were displayed after obtaining the final global separation vector. The experiments show the effectiveness and great robustness of the proposed algorithm.
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Published: 17 March 2011
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基于彩色图像的皮肤色素浓度提取算法
为了研究人体皮肤中最重要的2种色素:黑色素与血色素,提出一种基于光密度空间的图像通道差的算法,从单张彩色图像中自动提取黑色素与血色素的浓度分布.该算法以皮肤的结构和光学属性为理论基础,构建色素与图像的数学模型.整个算法先将输入图像分为若干个子区域.在每个子区域利用独立成份分析ICA技术计算分离向量,根据归纳的原则对分离向量进行合理性验证.将所有合理的分离向量重组,生成新的向量,从中找出偏差最小的作为最终的全局分离向量,并以此计算色素浓度分布图.结果表明,该算法获得了理想的效果,并具有很好的鲁棒性.
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