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Fingerprint image watermarking approach using DTCWT without corrupting minutiae

机译:使用DTCWT的指纹图像水印方法而不会破坏细节

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This paper proposes a new digital watermarking technique for fingerprint images using the Dual-Tree Complex Wavelet Transform (DTCWT). The watermark is embedded into the real and imaginary parts of the DTCWT wavelet coefficients. This work focuses on the study of watermarking techniques for fingerprint images that are collected from different angles without corrupting minutiae points. We investigate the effect of the watermark on the fingerprint features after the watermark embedding process. VeriFinger V5.0 is used to determine the matching score between the template and the watermarked images. The users identity is linked with the fingerprint features to add more authentication factors to the authentication process. The SHA2 hash function is used to encode the user identification number by generating the hash value and convert it into a binary image to construct the watermark data. The original fingerprint image is not required to extract watermark data. The proposed method has been tested using the CASIA fingerprint image database with 500 fingerprint images from 100 persons.
机译:本文提出了一种使用双树复数小波变换(DTCWT)的指纹图像数字水印技术。水印被嵌入DTCWT小波系数的实部和虚部。这项工作的重点是研究从不同角度收集的指纹图像的水印技术,而不会破坏细节点。我们研究了水印嵌入过程后水印对指纹特征的影响。 VeriFinger V5.0用于确定模板和水印图像之间的匹配分数。用户身份与指纹功能相关联,以向身份验证过程添加更多身份验证因素。 SHA2散列函数用于通过生成散列值来对用户标识号进行编码,并将其转换为二进制图像以构造水印数据。提取水印数据不需要原始指纹图像。使用CASIA指纹图像数据库对100个人的500幅指纹图像进行了测试。

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