49 research outputs found

    Palmprint Authentication System Based on Local and Global Feature Fusion Using DOST

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    Palmprint is the region between wrist and fingers. In this paper, a palmprint personal identification system is proposed based on the local and global information fusion. The local and global information is critical for the image observation based on the results of the relationship between physical stimuli and perceptions. The local features of the enhanced palmprint are extracted using discrete orthonormal Stockwell transform. The global feature is obtained by reducing the scale of discrete orthonormal Stockwell transform to infinity. The local and global matching distances of the two palmprint images are fused to get the final matching distance of the proposed scheme. The results show that the fusion of local and global features outperforms the existing works on the available three datasets

    Intensifying the Security of Multiomodal Biometric Authentication System using Watermarking

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    In Multimodal biometrics system two or more biometric attributes are combined which makes it far more secure than unimodal system as it nullifies all the vulnerabilities of it. But with the prompt ontogenesis of information technology, even the biometric data is not secure. There is one such technique that is implemented to secure the biometric data from inadvertent or deliberate attacks is known as Digital watermarking. This paper postulate an approach that is devise in both the directions of enlarging the security through watermarking technique and improving the efficiency of biometric identification system by going multimodal. Three biometric traits are consider in this paper two of them are physical traits i.e. ; face, fingerprint and one is behavioral trait (signature).The biometric traits are initially metamorphose using Discrete Wavelet and Discrete Cosine Transformation and then watermarked using Singular Value Decomposition. Scheme depiction and presented results rationalize the effectiveness of the scheme

    Characterization of palmprints by wavelet signatures via directional context modeling

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    2003-2004 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

    Finger Knuckle Analysis: Gabor Vs DTCWT

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    Knuckle biometrics is one of the current trends in biometric human identification which offers a reliable solution for verification. This paper analysis FKP recognition based on the behaviour of two different filtering and classification methods. Firstly, Gabor Filter Banks techniques are applied for finger knuckle print recognition and then the same database is analysed against Dual Tree Complex Wavelet Transform technique. The experiment is evaluated to identify finger knuckle images using PolyU FKP database of 7920 images. Finally, these two different systems are compared for false acceptance rate FAR, true acceptance, false rejection rate FRR and true rejection. Extensive experiments are performed to evaluate both the techniques, and experimental results show the pros and cons of using both the techniques for specific applications. DOI: 10.17762/ijritcc2321-8169.150518

    Curvelet Transform-Based Techniques For Biometric Person Identification

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    Biometric person identification refers to the recognition of a person based on the physical or behavioral traits. Palm print based biometric identification system is one of the low cost biometric systems, since the palm image can be obtained using low cost sensors, such as desktop scanners and web cameras. Because of ease of image acquisition of palm prints and identification accuracy, palm images are used in both uni- modal and multimodal biometric systems. A multi-scale and multi-directional representation is desirable to represent thick and scattered thin lines of a palm image. Multi-scale and multi-directional representation can also be used in image fusion, where two images of two different biometric traits can be fused to a single image to improve the identification accuracy. Face and palm images can be fused to keep the desired high pass information of the palm images and the low pass information of the face images. The Curvelet transform is a multi-scale and multi-directional geometric transform that provides a better representation of the objects with edges and requires a small number of curvelet coefficients to represent the curves. In this thesis, two methods using the very desirable characteristics of the curvelet transform are proposed for both the uni-modal and bi-modal biometric systems. A palm curvelet code (PCC) for palm print based uni-modal biometric systems and a pixel-level fusion method for face and palm based bi-modal biometric systems are developed. A simple binary coding technique that represents the structural information in curvelet directional sub-bands is used to obtain the PCC. Performance of the PCC is evaluated for both identification and verification modes of a palm print based biometric system, and then, the use of PCC in hierarchical identification is investigated. In the pixel-level fusion scheme for a bi-modal system, face and palm images are fused in the curvelet transform domain using mean-mean fusion rule. Extensive experimentations are carried out on three publicly available palm databases and one face database to evaluate the performance in terms of the commonly used metrics, and it is shown that the proposed methods provide a better performance compared to other existing methods

    Pose Invariant Face Recognition Using DT-CWT Partitioning and KPCA

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    In this paper the suitability of Dual Tree Complex Wavelet Transform for pose invariant Face Recognition is studied and a feature extraction frame work is proposed. This proposed framework will aid in design of Face Recognition system to address the challenging issue like Pose Variation. In contrast to the discrete wavelet Transform (DWT) the design of Dual Tree Complex Wavelet Transform is rugged to shift Invariance and poses good directional properties. These features of DT-CWT motivated to study their suitability for Face Feature Extraction, as the features of face are oriented in different directions. In this proposed frame work the Image is decomposed using DT-CWT and the features are extracted from low frequency band using Kernel Principal Component analysis (KPCA). To show the performance, the proposed method is tested on ORL Database. Satisfactory results are obtained using proposed method compared to existing state of art

    Process of Fingerprint Authentication using Cancelable Biohashed Template

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    Template protection using cancelable biometrics prevents data loss and hacking stored templates, by providing considerable privacy and security. Hashing and salting techniques are used to build resilient systems. Salted password method is employed to protect passwords against different types of attacks namely brute-force attack, dictionary attack, rainbow table attacks. Salting claims that random data can be added to input of hash function to ensure unique output. Hashing salts are speed bumps in an attacker’s road to breach user’s data. Research proposes a contemporary two factor authenticator called Biohashing. Biohashing procedure is implemented by recapitulated inner product over a pseudo random number generator key, as well as fingerprint features that are a network of minutiae. Cancelable template authentication used in fingerprint-based sales counter accelerates payment process. Fingerhash is code produced after applying biohashing on fingerprint. Fingerhash is a binary string procured by choosing individual bit of sign depending on a preset threshold. Experiment is carried using benchmark FVC 2002 DB1 dataset. Authentication accuracy is found to be nearly 97\%. Results compared with state-of art approaches finds promising

    Palmprint Identification Based on Generalization of IrisCode

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    The development of accurate and reliable security systems is a matter of wide interest, and in this context biometrics is seen as a highly effective automatic mechanism for personal identification. Among biometric technologies, IrisCode developed by Daugman in 1993 is regarded as a highly accurate approach, being able to support real-time personal identification of large databases. Since 1993, on the top of IrisCode, different coding methods have been proposed for iris and fingerprint identification. In this research, I extend and generalize IrisCode for real-time secure palmprint identification. PalmCode, the first coding method for palmprint identification developed by me in 2002, directly applied IrisCode to extract phase information of palmprints as features. However, I observe that the PalmCodes from the different palms are similar, having many 45o streaks. Such structural similarities in the PalmCodes of different palms would reduce the individuality of PalmCodes and the performance of palmprint identification systems. To reduce the correlation between PalmCodes, in this thesis, I employ multiple elliptical Gabor filters with different orientations to compute different PalmCodes and merge them to produce a single feature, called Fusion Code. Experimental results demonstrate that Fusion Code performs better than PalmCode. Based on the results of Fusion Code, I further identify that the orientation fields of palmprints are powerful features. Consequently, Competitive Code, which uses real parts of six Gabor filters to estimate the orientation fields, is developed. To embed the properties of IrisCode, such as high speed matching, in Competitive Code, a novel coding scheme and a bitwise angular distance are proposed. Experimental results demonstrate that Competitive Code is much more effective than other palmprint algorithms. Although many coding methods have been developed based on IrisCode for iris and palmprint identification, we lack a detailed analysis of IrisCode. One of the aims of this research is to provide such analysis as a way of better understanding IrisCode, extending the coarse phase representation to a precise phase representation, and uncovering the relationship between IrisCode and other coding methods. This analysis demonstrates that IrisCode is a clustering process with four prototypes; the locus of a Gabor function is a two-dimensional ellipse with respect to a phase parameter and the bitwise hamming distance can be regarded as a bitwise angular distance. In this analysis, I also point out that the theoretical evidence of the imposter binomial distribution of IrisCode is incomplete. I use this analysis to develop a precise phase representation which can enhance iris recognition accuracy and to relate IrisCode and other coding methods. By making use of this analysis, principal component analysis and simulated annealing, near optimal filters for palmprint identification are sought. The near optimal filters perform better than Competitive Code in term of d’ index. Identical twins having the closest genetics-based relationship are expected to have maximum similarity in their biometrics. Classifying identical twins is a challenging problem for some automatic biometric systems. Palmprint has been studied for personal identification for many years. However, genetically identical palmprints have not been studied. I systemically examine Competitive Code on genetically identical palmprints for automatic personal identification and to uncover the genetically related palmprint features. The experimental results show that the three principal lines and some portions of weak lines are genetically related features but our palms still contain rich genetically unrelated features for classifying identical twins. As biometric systems are vulnerable to replay, database and brute-force attacks, such potential attacks must be analyzed before they are massively deployed in security systems. I propose projected multinomial distribution for studying the probability of successfully using brute-force attacks to break into a palmprint system based on Competitive Code. The proposed model indicates that it is computationally infeasible to break into the palmprint system using brute-force attacks. In addition to brute-force attacks, I address the other three security issues: template re-issuances, also called cancellable biometrics, replay attacks, and database attacks. A random orientation filter bank (ROFB) is used to generate cancellable Competitive Codes for templates re-issuances. Secret messages are hidden in templates to prevent replay and database attacks. This technique can be regarded as template watermarking. A series of analyses is provided to evaluate the security levels of the measures
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