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Facial features detection in color images based on skin color segmentation

机译:基于肤色分割的彩色图像面部特征检测

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In case of intelligent biometric system facial features identification is a challenging task. Facial features like eye, mouth, lip are the critical factor to express human emotion. Face and facial features detection can be implemented automatically with the help of computer, but it is a difficult work. In this paper, a new frame work has been proposed for a fast and efficient detection of face and facial features like eyes, nose, mouth and lip from the color images. Here, the face image is given as input and facial features like eyes, mouth and lip are taken as output. The proposed algorithm increased the skin color segmentation and this method is based on three stages, face detection, region localization and facial features detection. The experimental results of the proposed method have been compared with RGB and HSI color space. The experimental results show that the proposed algorithm gives better results than the existing methods. The proposed method has eliminated the problem arise due to different pose, position of image, expressions and illumination variation problem. The average accuracy of the proposed algorithm is 97.69% and extraction of the facial features becomes easy using the proposed method from the color images.
机译:在智能生物识别系统的情况下,面部特征识别是一项艰巨的任务。眼,口,唇等面部特征是表达人类情感的关键因素。面部和面部特征检测可以在计算机的帮助下自动实现,但这是一项艰巨的工作。在本文中,已经提出了一种新的框架,用于从彩色图像中快速有效地检测面部和面部特征,例如眼睛,鼻子,嘴巴和嘴唇。在此,将脸部图像作为输入,将脸部特征(如眼睛,嘴巴和嘴唇)作为输出。所提出的算法增加了肤色分割,该方法基于面部检测,区域定位和面部特征检测三个阶段。将该方法的实验结果与RGB和HSI颜色空间进行了比较。实验结果表明,与现有方法相比,该算法具有更好的效果。所提出的方法消除了由于姿势,图像位置,表情和光照变化问题而引起的问题。所提算法的平均准确率为97.69%,并且使用所提方法从彩色图像中提取面部特征变得容易。

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