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Investigation of Feature Selection Techniques for Face Recognition Using Feature Fusion Model

机译:基于特征融合模型的人脸识别特征选择技术研究

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This study investigates various feature selection techniques for face recognition. Biometric based authentication system protects access to resources and has gained importance, because of their reliable, invariant and discriminating features. An automated biometric system is based on physiological or behavioral human characteristics for protected access. Biometric trait such as palmprint, iris, hand, voice, face fingerprint, or signature is used to authenticate a person's claim. Of the biometrics, face recognition is gaining popularity due to its simple method of capturing the image using cameras. However the number of features generated is high leading to higher computation time. Using feature selection technique it is shown that recognition rate improves.
机译:这项研究调查了用于面部识别的各种特征选择技术。基于生物特征的身份验证系统可保护对资源的访问,并且由于其可靠,不变和可区分的功能而变得越来越重要。自动化的生物特征识别系统基于生理或行为人类特征来保护访问。诸如掌纹,虹膜,手,声音,面部指纹或签名之类的生物特征被用来验证一个人的主张。在生物识别技术中,人脸识别由于其使用相机捕获图像的简单方法而变得越来越流行。但是,生成的特征数量很多,导致计算时间更长。使用特征选择技术表明识别率提高了。

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