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首页> 外文期刊>American journal of applied sciences >Faces Detection using Skin Color, Region-Props, Bounding-Box and Neural Networks System
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Faces Detection using Skin Color, Region-Props, Bounding-Box and Neural Networks System

机译：使用肤色，区域属性，边界框和神经网络系统进行人脸检测

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摘要

Face detection is an important prior step for face recognition system which is widely used in security systems, face verification systems, telecommunication, video surveillance, facial expressions recognition, status authentication, etc. The proposed system is applied on many images which contain persons and extract the faces out of there automatically. The skin color, region-props and bounding-box are used as preprocessing tools for extracting regions. The Neural Networks (NNT) are used to recognize these regions are faces or not. This system has the ability to detect faces with various image conditions: Different poses and facial expirations, different and complex backgrounds and different luminance and lighting conditions. The system is tested on several color images. The detection rates for used databases are 67.6% for images which has background non-luminous, 88% for very dense images and 100% for non-dense images with a luminous background.
机译：人脸检测是人脸识别系统的重要的先决步骤，该系统已广泛应用于安全系统，人脸验证系统，电信，视频监控，人脸表情识别，状态验证等领域。该系统适用于包含人和提取物的许多图像脸自动离开那里。皮肤颜色，区域属性和边界框用作提取区域的预处理工具。神经网络（NNT）用于识别这些区域是否为人脸。该系统具有检测具有各种图像条件的面部的能力：不同的姿势和面部呼气，不同且复杂的背景以及不同的亮度和照明条件。该系统已在多个彩色图像上进行了测试。对于背景不发光的图像，使用过的数据库的检测率为67.6％，对于非常密集的图像为88％，对于具有发光背景的非密集图像为100％。

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