Biometric Template Spoofing Detection Using Sparse Watermarking Scheme

No Abstrac

Security of Biometric Data Using Compressed Watermarking Technique

This paper has focus on biometric data security over open communication channel of biometric system. Here biometric data is encoded using cs theory and wavelet based embedding technique. The biometric data is convert into encoded sparse measurements which is generating using SVD, random seed and uniform quantization process. Then these encoded sparse measurements are embedding into the host color biometric data using wavelet based watermarking technique. This proposed technique has explored dimension reduction and computational security provided by compressive sensing. This proposed technique has also helps to compressed and to send secret data over noisy communication channel of biometric system against various attacks. The proposed technique provides more security compare to existed technique in literature due to CS theory. The novelty of proposed technique is that, watermark iris image information is compressed and encoded using CS theory and uniform quantization.DOI:http://dx.doi.org/10.11591/ijece.v4i5.664

Robust and Secure Watermarking Using Sparse Information of Watermark for Biometric Data Protection

Biometric based human authentication system is used for security purpose in many organizations in the present world. This biometric authentication system has several vulnerable points. Two of vulnerable points are protection of biometric templates at system database and protection of biometric templates at communication channel between two modules of biometric authentication systems. In this paper proposed a robust watermarking scheme using the sparse information of watermark biometric to secure vulnerable point like protection of biometric templates at the communication channel of biometric authentication systems. A compressive sensing theory procedure is used for generation of sparse information on watermark biometric data using detail wavelet coefficients. Then sparse information of watermark biometric data is embedded into DCT coefficients of host biometric data. This proposed scheme is robust to common signal processing and geometric attacks like JPEG compression, adding noise, filtering, and cropping, histogram equalization. This proposed scheme has more advantages and high quality measures compared to existing schemes in the literature

Robust watermarking technique using different wavelet decomposition levels for signature image protection

This paper proposed a non-blind watermarking technique based on different wavelet decomposition levels for biometric image protection.In this technique, a biometric image is used as a watermark instead of a standard image, logo or random noise pattern type watermark.For watermark embedding, the original host image and the watermark biometric image are transformed into various levels of wavelet coefficients.The watermark biometric image is embedded into the host image by modifying the values of the wavelet coefficients of the host image using the values of wavelet coefficients of the watermark biometric image.Experimental results demonstrated that the proposed technique was able to withstand various watermarking attacks. The novelty of the proposed technique is that it is used to transform coefficients of the watermark biometric image instead of the Pseudo Noise sequences or any other feature extraction technique

ROBUST WATERMARKING TECHNIQUE USING DIFFERENT WAVELET DECOMPOSITION LEVELS FOR SIGNATURE IMAGE PROTECTION

This paper proposed a non-blind watermarking technique based on different wavelet decomposition levels for biometric image protection. In this technique, a biometric image is used as a watermark instead of a standard image, logo or random noise pattern type watermark. For watermark embedding, the original host image and the watermark biometric image are transformed into various levels of wavelet coefficients. The watermark biometric image is embedded into the host image by modifying the values of the wavelet coefficients of the host image using the values of wavelet coefficients of the watermark biometric image. Experimental results demonstrated that the proposed technique was able to withstand various watermarking attacks. The novelty of the proposed technique is that it is used to transform coefficients of the watermark biometric image instead of the Pseudo Noise sequences or any other feature extraction technique.

An efficient medical image watermarking scheme based on FDCuT–DCT

In this paper, a blind medical image watermarking scheme based on Fast Discrete Curvelet Transform (FDCuT) and Discrete Cosine Transform (DCT) is proposed. FDCuT is applied on the medical image to get different frequency coefficients of its curvelet decomposition. On the high frequency curvelet coefficients of the medical image, block wise DCT is applied to get different frequency coefficients. Then mid band frequency coefficients of the medical image are modified by White Gaussian Noise (WGN) sequences according to watermark bit to get watermarked medical image. At extraction end, blind recovery of watermark data is performed by correlation of WGN sequences. The proposed scheme is tested for its effectiveness on various types of medical images such as X-ray, Ultrasound (US), Magnetic Resonant Imaging (MRI) and Computerized Tomography (CT). Result analysis shows that imperceptibility of watermarked medical image is better as PSNR is above 45 dB for all types of the medical images. In addition, the robustness of the scheme is better than an existing scheme for a similar set of medical images in terms of Normalized Correlation (NC). Experimental results show that scheme is robust to geometric attacks, signal processing attacks and JPEG compression attacks. An analysis is also carried out to verify the performance of the proposed scheme to support binary watermarks with different details in it: text and logos. Moreover, the proposed scheme resulted in zero false positive rate when tested on 100 non-watermarked images