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Hybrid Component-Based Face Recognition System

机译：基于混合组件的人脸识别系统

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摘要

Face recognition system is a fast growing research field because of its potential as an eminent tool for security surveillance, human-computer interaction, identification declaration and other applications. Face recognition techniques can be categorized into 3 categories namely holistic approach, feature-based approach, and hybrid approach. In this paper, a hybrid component-based system is proposed. Linear discriminant analysis (LDA) is used to extract the feature from each component. The outputs from the individual components are then combined to give the final recognition output. Two methods are used to obtain the components, namely the facial landmarks and the sub-images. It was found out that the fusion of the components does improve the recognition rate compared to individual results of each component. From the sub-image method, it can be seen that as the size of the components get smaller, the recognition rate tends increase but not always.
机译：人脸识别系统是一个快速发展的研究领域，因为它具有作为安全监控，人机交互，识别声明和其他应用程序的杰出工具的潜力。人脸识别技术可分为三类，即整体方法，基于特征的方法和混合方法。本文提出了一种基于混合组件的系统。线性判别分析（LDA）用于从每个组件中提取特征。然后将各个组件的输出进行组合，以提供最终的识别输出。两种方法用于获取分量，即面部标志和子图像。已经发现，与每个组件的单独结果相比，组件的融合确实提高了识别率。从子图像方法可以看出，随着组件尺寸的变小，识别率趋于增加，但并非总是如此。

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