Securing Multiple Biometric Data Using SVD and Curvelet-Based Watermarking

2018 ◽  
Vol 12 (4) ◽  
pp. 35-53 ◽  
Author(s):  
Rohit M. Thanki ◽  
Komal Rajendrakumar Borisagar
Keyword(s):  
Speech Signal ◽  
Curvelet Transform ◽  
Image Authentication ◽  
Recognition System ◽  
Singular Value ◽  
Fingerprint Recognition ◽  
Security And Privacy ◽  
Fingerprint Image ◽  
Biometric Data ◽  
Value Decomposition

The security and privacy of biometric data in multibiometric systems has become a hot research topic. In this paper, a singular value decomposition (SVD) and fast discrete curvelet transform (FDCuT)-based watermarking scheme for authenticity of fingerprint image using watermark speech signal has been proposed and analyzed. This scheme also provides security to watermark speech signal, which is inserted into the fingerprint image. This proposed scheme has a number of steps including fingerprint image authentication using watermark speech signal. The human speech signal is taken as secret watermark information and inserting into the human fingerprint image in the proposed scheme. The singular value of high frequency curvelet coefficients of the host fingerprint image is modified according to watermark speech signal to get secured and watermarked fingerprint image. The analysis results show that the performance of fingerprint recognition system is not affected by inserted watermark speech signal into host fingerprint image.

Application of Fingerprint-Matching Algorithm in Smart Gun Using Touch-Less Fingerprint Recognition System

2020 ◽  
pp. 122-128
Author(s):  
Saifullah Khalid
Keyword(s):  
Recognition System ◽  
Fingerprint Recognition ◽  
Fingerprint Matching ◽  
Fingerprint Image ◽  
Matching Algorithm ◽  
Latent Fingerprint ◽  
Recognition Systems

Fingerprint recognition systems are widely used in the field of biometrics. Many existing fingerprint sensors acquire fingerprint images as the user's fingerprint is contacted on a solid flat sensor. Because of this contact, input images from the same finger can be quite different and there are latent fingerprint issues that can lead to forgery and hygienic problems. For these reasons, a touchless fingerprint recognition system has been investigated, in which a fingerprint image can be captured without contact. While this system can solve the problems which arise through contact of the user's finger, other challenges emerge.

A self-embedding fragile image authentication based on singular value decomposition

2020 ◽  
Vol 79 (35-36) ◽  
pp. 25969-25988
Author(s):  
Jau-Ji Shen ◽  
Chin-Feng Lee ◽  
Fang-Wei Hsu ◽  
Somya Agrawal
Keyword(s):  
Singular Value Decomposition ◽  
Image Authentication ◽  
Singular Value ◽  
Value Decomposition

A Grayscale Image Vulnerability Authentication System Based on Compressed Sensing

2015 ◽  
Vol 738-739 ◽  
pp. 533-537
Author(s):  
Xu Zhan ◽  
Yue Rong Lei ◽  
Hui Ming Zeng ◽  
Jian Ling Chen
Keyword(s):  
Compressed Sensing ◽  
Image Authentication ◽  
Singular Value ◽  
Grayscale Image ◽  
Arnold Transform ◽  
Edge Information ◽  
Observation Matrix ◽  
Image Edge ◽  
Authentication System ◽  
Value Decomposition

In this paper, we study compressed sensing algorithm and image authentication algorithm, present a grayscale image vulnerability authentication system based on compressed sensing. The system extracts the original grayscale image edge information by prewitt algorithm and observes the edge information by compressed sensing algorithm of OMP to generate the observation matrix . Then, the system scrambles the observation matrix by arnold transform algorithm and embeds it into the original grayscale image by singular value decomposition algorithm. We make experiment in order to test the system. The result is shown that the algorithm has good imperceptibility and can resist copying attack.

Research and Evaluation of Multispectral Feature Selection and Fusion Model for Palmprint Recognition

2013 ◽  
Vol 411-414 ◽  
pp. 1291-1294
Author(s):  
Ying Xu ◽  
Fei Luo
Keyword(s):  
Bp Neural Network ◽  
Back Propagation ◽  
Recognition System ◽  
Singular Value ◽  
Personal Identification ◽  
Palmprint Recognition ◽  
Fusion Model ◽  
Network Method ◽  
Robust Recognition ◽  
Value Decomposition

Palmprint is widely used in personal identification for an accurate and robust recognition. Multispectral palmprint images capture under different illumination, including Red, Green, Blue and Infrared maybe contribute to the recognition results. However, the evaluation of selection and fusion of how this different spectral images can contribute to improve the robustness of the recognition system is imperative. In this paper, a novel wavelet-based multispectral fusion strategy is presented firstly to obtain the fused images; then block singular value decomposition (B-SVD) is applied for feature extraction; Finally back propagation (BP) neural network method is adopted for authentication. The proposed algorithm is evaluated on PolyU database which contains palmprint images from 500 individuals from four independent frequent band. The obtained results show robustness of our multispectral palmprint image fusion and selection model in comparison with the single spectral palmprint image that presented in the literature.

Study of Fingerprint Image Feature Extraction Algorithm

2014 ◽  
Vol 519-520 ◽  
pp. 577-580
Author(s):  
Shuai Yuan ◽  
Guo Yun Zhang ◽  
Jian Hui Wu ◽  
Long Yuan Guo
Keyword(s):  
Feature Extraction ◽  
Recognition System ◽  
Fingerprint Recognition ◽  
Image Feature ◽  
Feature Points ◽  
Orientation Field ◽  
Fingerprint Image ◽  
Image Feature Extraction ◽  
Feature Extraction Algorithm ◽  
Extraction Algorithm

Fingerprint image feature extraction is a critical step to fingerprint recognition system, which studies topological structure, mathematical model and extraction algorithm of fingerprint feature. This paper presents system design and realization of feature extraction algorithm for fingerprint image. On the basis of fingerprint skeleton image, feature points including ending points, bifurcation points and singular points are extracted at first. Then false feature points are detected and eliminated by the violent changes of ambient orientation field. True feature points are marked at last. Test result shows that the method presented has good accuracy, quick speed and strong robustness for realtime application.

scholarly journals Medical Image Authentication using Stationary Wavelet Transformation and Singular Value Decomposition

2019 ◽  
Vol 8 (3) ◽  
pp. 953-958
Keyword(s):  
Singular Value Decomposition ◽  
Medical Image ◽  
Wavelet Transformation ◽  
Medical Images ◽  
Signal To Noise Ratio ◽  
Image Authentication ◽  
Transformation Method ◽  
Singular Value ◽  
Invariance Property ◽  
Value Decomposition

he proposed paper work is implemented using Stationary Wavelet Transformation (SWT) with Singular Value Decomposition (SVD).Even though, there are many other transformations, the Stationary Wavelet Transformation method is chosen for its shift invariance property. The designed method has three steps; the first step is the decomposing of the Medical image into sub-bands using SWT to find the value of sub band and as a second step is to apply SVD, third step will combine both the images with scaling factor. The experiments were conducted over gray scale of MRI and CT Medical images. The statistics of proposed method indicates that imperceptibility of Watermarked Medical images have a Peak Signal to Noise Ratio (PSNR) value of 50 DB for medical images. The robustness is ensured by having Correlation Coefficient (CC) of 1 for the retrieved watermark images. Security for the watermark is extended by encrypting the watermark with chaotic sequence.

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