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Combination approach to score level fusion for Multimodal Biometric system by using face and fingerprint

机译:基于面部和指纹的多模态生物特征识别系统分数水平融合的组合方法

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Biometric System is used for person's recognition and identification for various applications. The Biometric system is unimodal and multimodal biometric system. Unimodal Biometric suffers from Noisy data, Intra class variation, non versality, spoofing etc. These drawbacks can remove by using Multimodal Biometric system. We developed the multimodal Biometric system by using Face and fingerprint Multimodalities. This system takes the advantage of individual Biometric System. This paper presents the fusion of face and fingerprint modalities at score level fusion. The system extracts the features and these features are then used for matching. Euclidean distance matcher is used for Face and Finger print modalities. Fingerprint recognition can be done with the help of minutiae matching and Gabor filter. The Face feature is extracted with the help of PCA (Principle Component Analysis) for dimensionality Reduction. Then the match scores are Normalized and sum score level fusion is used to develop the system. The proposed approach provides the better results. The Recognition Rate is increased and the error rate is decreased by with the help of this system.
机译:生物识别系统用于人们对各种应用的识别和识别。生物识别系统是单峰和多峰生物识别系统。单峰生物特征遭受噪声数据,类内变异,非通用性,欺骗等困扰。使用多峰生物特征系统可以消除这些缺陷。我们通过使用人脸和指纹多模式开发了多模式生物识别系统。该系统利用了个体生物识别系统的优势。本文介绍了在分数级别融合中人脸和指纹模态的融合。系统提取特征,然后将这些特征用于匹配。欧几里德距离匹配器用于面部和指纹模式。指纹识别可以通过细节匹配和Gabor过滤器完成。脸部特征是借助PCA(原理成分分析)提取的,以减少维数。然后对比赛分数进行归一化,并使用总和得分等级融合来开发系统。所提出的方法提供了更好的结果。借助此系统,可以提高识别率,并减少错误率。

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