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CNN Based Iris Recognition System: A Novel Approach

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Document pages: 8 pages

Abstract: Iris image is the most important and unique feature in the field of biometrics and a powerful tool for human identification because of its strong and unique textual information. Extracting these prominent features is the main advancement in recognizing the iris biometric modality. The problems we faced in computer vision can be overcome with the success in deep learning technology. The features learned using CNN was found to be very much useful in the Iris recognition system. This work mainly focused on evaluating the extracted features learned from the proposed convolutional neural network model and Softmax Classifier. The selective features of the source image are extracted by this Softmax Classifier without any preliminary domain knowledge. The input image represents the localized, normalized, and then enhanced iris region, then it will be classified into N classes. The performance of the system has been experimented on, with two public datasets viz IITD and CASIA. An accuracy of 96 is obtained by using this proposed system.

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