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首页> 外文会议>International Conference on Information Communication and Embedded Systems >TEMPLATE MATCHING FOR DETECTION RECOGNITION OF FRONTAL VIEW OF HUMAN FACE THROUGH MATLAB
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TEMPLATE MATCHING FOR DETECTION RECOGNITION OF FRONTAL VIEW OF HUMAN FACE THROUGH MATLAB

机译：用Matlab检测与识别人脸前视图的模板

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摘要

Human face is an important object in an image database due to its unique features (eyes, mouth, nose etc.) in every human being. The detection & recognition of a face in an image using template matching is one of the profound research interest in the field of image processing. Various approaches have been proposed in the literature to extract the visual facial features based on texture, color, shape, sketch & pose variance etc. for face detection in color images. This paper describes an approach of face detection technique that includes major characteristics such as lightening compensation based on luminance (Y) & chrominance (Cr), Color segmentation, skin-tone statistics & eye-mouth region computation. A template matching algorithm using cross correlation method for locating & recognizing a face has been applied on various face candidates to match the template with right face candidate. Thus, the presented work is divided into three steps: Face detection, Computation of template matching & Face recognition. The performance of given approach has been evaluated on the basis of run time & accuracy. The simulation result shows that the defined model is efficient in terms of accuracy which is 81% and the false alarms are reduced.
机译：由于其每个人类的独特功能（眼睛，嘴巴，鼻子等），人脸是图像数据库中的重要对象。使用模板匹配的图像中面部的检测和识别是图像处理领域的深刻研究兴趣之一。在文献中提出了各种方法，以基于纹理，颜色，形状，草图和姿势等提取视觉面部特征，用于彩色图像中的面部检测。本文描述了一种面部检测技术的方法，包括基于亮度（Y）和色度（CR），彩色分割，肤色统计和眼口计算的主要特征。一种模板匹配算法使用跨相关方法定位和识别脸部已经应用于各种面部候选，以匹配具有右面候选的模板。因此，所呈现的工作分为三个步骤：面部检测，计算模板匹配和面部识别。在运行时间和准确性的基础上评估了给定方法的性能。仿真结果表明，定义的模型在高精度方面是有效的，即81％，误报是减少的。

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