Manonmani Panneerselvam, R. Divya, V. Vijayalakshmi
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引用次数: 2
摘要
提出的多生物识别技术将手指静脉作为指纹和虹膜的附加生物特征。手指静脉是非侵入性的,增加了安全性。此外,为了克服对多生物特征系统模板系统数据库的欺骗攻击,现有系统进一步着重于通过实现数字水印技术来保护生物特征模板。采用奇异值分解(SVD)和离散小波变换(DWT)技术进行水印。利用MATLAB工具对PSNR、NCC和SSIM等性能指标进行了仿真。现有技术对JPEG压缩、中值滤波和高斯噪声、椒盐噪声等噪声的鲁棒性较差,且离散小波变换存在平移不变性问题。为了克服这一问题,本课题采用双树复小波变换(DTCWT)实现多层水印技术。对偶树复小波变换的优点提高了去噪性能。通过验证来证明安全性。利用MATLAB对双树复小波变换(Dual Tree Complex Wavelet Transform, DTCWT)的PSNR、NCC和SSIM等性能指标进行了仿真,得到了双树复小波变换与DTCWT的FAR、FRR、System Accuracy等安全措施参数以及ROC比较曲线。
Multilevel watermarking technique for securing multibiometric templates using DTCWT and SVD
The proposed multibiometric technique implements finger vein as an additional biometric trait along with fingerprint and iris. Finger vein is non-invasive in nature and increases security. In addition, in order to overcome spoofing attack on system database of multibiometric system template, the existing system further focuses on securing the Biometric template by implementing Digital watermarking technique. Watermarking is carried out by using Singular Value Decomposition (SVD) and Discrete Wavelet Transform (DWT) techniques. The performance metrics such as PSNR, NCC and SSIM is simulated using MATLAB tool. The Existing technique is not robust against JPEG compression, median filtering and noise addition like Gaussian noise, salt & pepper noise etc., and also the Discrete Wavelet Transform has Lack of Shift Invariance problem. To overcome this problem, this project is implemented with Dual Tree Complex Wavelet Transform (DTCWT) in multilevel watermarking technique. The advantage of Dual Tree Complex Wavelet Transform improves denoising performance. The Authentication is implemented to prove the security. The performance metrics such as PSNR, NCC and SSIM is simulated using MATLAB for the Dual Tree Complex Wavelet Transform (DTCWT) and the security measures parameters like FAR, FRR, System Accuracy and the ROC comparison curve of the DWT and DTCWT are obtained.