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提出了一种新的皮肤分割和人脸特征提取方法…

于 2023-07-24 发布 文件大小:448.16 kB
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提出一种新的非线性变换的彩色空间 ″″, 利用次高斯概率分布函数拟合皮肤色度信息, 得到候选区 YC C r b 域。为了排除候选区域中的非人脸, 首先根据均值和方差信息分割出候选区域中的纹理特征信息, 再通过多尺度 ) ( 信息定位眼睛, 然后根据人脸特征的几 形态边缘检测算子检测候选区域的边缘, 利用 边缘方向 PCA PCAED ( ) 何形状信息定位其他特征 鼻、嘴 , 通过这些几何特征信息对肤色分割得到的候选区域进行验证, 最终得到正确 的人脸区域。利用3 个实验数据集测试该算法, 并与其它相应的算法相比较, 提出的非线性彩色空间对于肤色分 割具有很好的效果, 且对光照和姿态具有良好的不变性。另外, 利用 信息和几何特征信息检测人脸特征 PCAED 具有很高的定位精度, 定位检测率优于其他方法。实验结果表明, 该算法具有定位准确率高, 漏检率和误检率低 等特点。- A novel approach for skin segmentation and facial feature extraction is proposed The proposed skin segmentation is a method for integrating the chrominance components of ″″ . ″″ r b r b nonlinear YC C color model The chrominance components of nonlinear YC C color space , are modeled using a subgaussian probability density function and then the face skin is seg . , mented based on this function In order to authenticate the face candidate regions firstly tex ture information in face candidate regions is segmented using mean and variance of luminance ,

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