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An Adept Segmentation Algorithm and Its Application to the Extraction of Local Regions Containing Fiducial Points

机译:一种擅长的分割算法及其在含基准点的局部区域提取的应用

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Locating human fiducial points like eyes and mouth in a frontal head and shoulder image is an active research area for applications such as model based teleconferencing systems, model based low bit rate video transmission, computer based identification and recognition systems. This paper proposes an adept and efficient rule based skin color region extraction algorithm using normalized r-g color space. The given scheme extracts the skin pixels employing a simple quadratic polynomial model and some additional color based rules to extract possible eye and lip regions. The algorithm refines the search for fiducial points by eliminating falsely extracted feature components using spatial and geometrical representations of facial components. The algorithm described herein has been implemented and tested with 311 images from FERET database with varying light conditions, skin colors, orientation and tilts. Experimental results indicate that the proposed algorithm is quite robust and leads to good facial feature extraction.
机译:在正面和肩部图像中定位人的基准点,是一种正面头部和肩部图像是基于模型的远程专家化系统,基于模型的低比特率视频传输,基于计算机的识别和识别系统的应用的活跃研究领域。本文提出了一种使用归一化R-G颜色空间的熟练和高效的基于规则的肤色提取算法。给定的方案提取采用简单二次多项式模型的皮肤像素和一些额外的基于颜色的规则来提取可能的眼睛和唇部区域。通过使用面部部件的空间和几何表示来消除虚假提取的特征组件,算法通过消除虚假提取的特征组分来精确搜索基准点。本文描述的算法已经实现和测试,用来自Feret数据库的311图像进行了测试,具有不同的光线,肤色,方向和倾斜。实验结果表明,所提出的算法非常稳健,导致好面部特征提取。

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