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

机译:新型的基于内容的大规模多模式生物识别系统方法

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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)系统吸引了研究人员的极大注意力,因为它能够有效地识别大型数据库中的图像,并且对现实世界中的应用程序的需求也在不断增长。许多人认为,生物特征识别是CBIR最具潜力的应用之一。但是,迄今为止,尚未发表有关基于内容的多模式生物识别系统的研究工作。在该建议中,提出了一种基于内容的多模式生物特征识别系统,该系统将颜色,纹理和形状特征组合在一起以提高系统的识别精度。所提出的基于内容的特征融合方法用于人脸识别的初步结果表明,它具有提高大型多模式生物特征识别系统的识别性能的潜力。

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