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首页> 外文会议>2010 18th Iranian Conference on Electrical Engineering >Optimized fuzzy system using genetic algorithm to detect faces in color images
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Optimized fuzzy system using genetic algorithm to detect faces in color images

机译：基于遗传算法的彩色图像优化模糊系统

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摘要

A human face detection method for color images is presented in this paper. The system is composed of three subsystems: skin color segmentation, lip color segmentation and face blobs selection subsystem. Whole these algorithms are fuzzy rule base ones, which are designed empirically, and then optimized by genetic algorithm. In the first stage, skin color regions are selected in the input image. Within each of the skin area, lip pixels are searched using second subsystem, and applied as a feature to identify face candidates in the skin regions. Utilizing the lip area and position relative to the skin area, and face shape information, the third subsystem is materialized to choose face blobs. To precise evaluation of the proposed system, the false positive and false negative of each subsystem, are reported for the empirically designed system as well as the optimized system. Obtained results show a remarkable decrease in false positive and false negative for optimized algorithms compared to empirically designed ones. Finally, 98% detection rate is achieved using proposed method.
机译：提出了一种彩色图像人脸检测方法。该系统由三个子系统组成：皮肤颜色分割，嘴唇颜色分割和脸部斑点选择子系统。所有这些算法都是模糊规则库，经过经验设计，然后通过遗传算法进行优化。在第一阶段，在输入图像中选择肤色区域。在每个皮肤区域内，使用第二个子系统搜索嘴唇像素，并将其用作特征以识别皮肤区域中的人脸候选对象。利用相对于皮肤区域的嘴唇区域和位置以及脸部形状信息，实现了第三子系统来选择脸部斑点。为了精确评估所提出的系统，针对经验设计的系统以及优化的系统，报告了每个子系统的假阳性和假阴性。获得的结果表明，与经验设计的算法相比，优化算法的误报率和误报率显着降低。最终，该方法检测率达到98％。

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