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Classifying Iris Image Based on Feature Extraction and Encryption using Bio-Chaotic Algorithm (BCA)

机译:使用生物混沌算法基于特征提取和加密进行分类虹膜图像(BCA)

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The classification of the iris image based on feature extraction algorithms like SIFT i.e Scale-Invariant Feature Transform. The SIFT algorithm helps to retrieve macro features from the iris template. Then the iris images which are stored into the database undergoes SIFT feature extraction technique so that they can be compared with the input image provided to the user. The images which fulfill the criteria of maximum feature matching are retrieved and display. The input image is then divided into parts so as to apply the Bio-Chaotic Algorithm. Firstly image is classified and then randomly one block is selected to hide secret message into it and encrypting the whole image using the same key. The graph of both original as well as encrypted iris image is generated so that one can see the difference after the encryption process. Only authorize user knows about the random block that's why attacker fails to fraud attack. The decryption process is reverse of encryption process. Then, the encrypted image is send to the receiver via e-mail, so that at the receiver end decryption can be done securely. The use of bio-chaotic stream cipher which will help to encrypt the iris images and store them securely using biometric key and bio-chaotic function.
机译:基于特征提取算法的虹膜图像的分类,如SIFT I.E尺度不变特征变换。 SIFT算法有助于从IRIS模板检索宏功能。然后将存储到数据库中的虹膜图像经历SIFT特征提取技术,使得它们可以与提供给用户提供的输入图像进行比较。检索符合最大特征匹配标准的图像并显示。然后将输入图像分成部分,以便应用生物混沌算法。首先是分类的图像,然后选择一个块以将秘密消息隐藏到它中并使用相同的键加密整个图像。生成原始和加密虹膜图像的图形,使得可以在加密过程之后看到差异。仅授权用户知道随机块,这就是攻击者无法欺诈攻击的原因。解密过程是加密过程的反向。然后,通过电子邮件将加密图像发送到接收器,因此可以安全地完成在接收器结束解密。使用生物混沌流密码,这将有助于加密虹膜图像并使用生物识别密钥和生物混沌功能安全地存储它们。

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