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    Detecting Iris Liveness with Batch Normalized Convolutional Neural Network

    Min Long1,2,*, Yan Zeng1

    CMC-Computers, Materials & Continua, Vol.58, No.2, pp. 493-504, 2019, DOI:10.32604/cmc.2019.04378

    Abstract Aim to countermeasure the presentation attack for iris recognition system, an iris liveness detection scheme based on batch normalized convolutional neural network (BNCNN) is proposed to improve the reliability of the iris authentication system. The BNCNN architecture with eighteen layers is constructed to detect the genuine iris and fake iris, including convolutional layer, batch-normalized (BN) layer, Relu layer, pooling layer and full connected layer. The iris image is first preprocessed by iris segmentation and is normalized to 256×256 pixels, and then the iris features are extracted by BNCNN. With these features, the genuine iris and fake iris are determined by… More >

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