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A Novel Content Based Methodology for a Large Scale Multimodal Biometric System

机译:基于大规模的多数制生物识别系统的基于新的基于内容的方法

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Recently, Content Based Image Retrieval (CBIR) system has drawn enormous attention of researchers because of its efficiency in recognizing images from large databases as well as growing demand from real world applications. According to many, biometrics recognition is one of the most potential applications of CBIR. However, no research work has been published up to date on content based multimodal biometric systems. In this proposal, a content based multimodal biometric system, where color, texture, and shape features are combined to enhance the recognition accuracy of the system, is proposed. The preliminary result of the proposed content based feature fusion method for face recognition demonstrates its potential to boost up the recognition performance of a large scale multimodal biometric system.
机译:最近,基于内容的图像检索(CBIR)系统由于其在识别来自大型数据库的图像以及从现实世界应用而越来越多的需求而汲取了研究人员的巨大关注。根据许多,生物识别是CBIR最潜在的应用之一。但是,没有关于基于内容的多模式生物识别系统的研究工作已发布。在该提议中,提出了一种基于内容的多模式生物识别系统,其中组合着颜色,纹理和形状特征以增强系统的识别精度。面部识别所提出的基于内容的特征融合方法的初步结果表明了其促进大规模多模式生物识别系统的识别性能的可能性。

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