A proposed framework for robust face identification system

2014 9th International Conference on Computer Engineering & Systems (ICCES) Pub Date : 2014-12-01 DOI:10.1109/ICCES.2014.7030929

N. Semary, Ahmed F. Gad

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引用次数: 4

Abstract

Human face is the most representative part of body that can be used to differentiate one person among others. Accurate face identification system is still a challenge to Image Processing and Pattern Recognition researchers. In this paper, a complete framework for face-based personal identification system is proposed. The proposed frame work is composite of three basic stages; face skin detection (FSD), facial features positioning (FFP), representative features extraction (RFE) and face matching (FM). For FSD stage, RGB-H-CbCr color model is used after a comparative study between different color models. Enhanced Haar-like features are utilized for FFP stage. After accurate features positioning, the representative features are calculated using the centers of eyes, nose and mouth organs. The experimental results of this paper depict that the proposed frame work accurately identify persons of The Center for Vital Longevity Face Database. The proposed system could Identify the correct person with 40 saved image with accuracy 98%, while it could reject wrong persons with accuracy 98.17%. The overall accuracy of correct identification reaches 98.14%.

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提出了一种鲁棒人脸识别系统框架

人脸是人体最具代表性的部分，可以用来区分一个人。准确的人脸识别系统仍然是图像处理和模式识别研究人员面临的一个挑战。本文提出了一个完整的基于人脸的个人身份识别系统框架。提出的框架由三个基本阶段组成;人脸皮肤检测(FSD)、人脸特征定位(FFP)、代表性特征提取(RFE)和人脸匹配(FM)。FSD阶段，通过对不同颜色模型的比较研究，采用RGB-H-CbCr颜色模型。增强的haar样特征用于FFP阶段。经过准确的特征定位后，利用眼、鼻、口器官的中心计算出具有代表性的特征。实验结果表明，该框架能准确识别长寿中心人脸数据库中的人脸。该系统能以98%的准确率从40张保存的图像中识别出正确的人，而拒绝错误的人的准确率为98.17%。正确识别的总体正确率达到98.14%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2014 9th International Conference on Computer Engineering & Systems (ICCES)

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