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Journal ArticleDOI

Multiresolution Feature Based Subspace Analysis for Fingerprint Recognition

25 Feb 2010-International Journal of Computer Applications (Foundation of Computer Science FCS)-Vol. 1, Iss: 13, pp 1-4

TL;DR: A multiresolution feature based subspace technique for fingerprint recognition that computes the core point of fingerprint and crops the image to predefined size and is effective and efficient in extracting the features.

AbstractThe image intensity surface in an ideal fingerprint image contains a limited range of spatial frequencies, and mutually distinct textures differ significantly in their dominant frequencies. This paper presents a multiresolution feature based subspace technique for fingerprint recognition. The technique computes the core point of fingerprint and crops the image to predefined size. The multiresolution features of aligned fingerprint are computed using 2-D discrete wavelet transform. LL component in wavelet decomposition is concatenated to form the fingerprint feature. Principal component analysis is performed on these features to extract the features with reduced dimensionality. The algorithm is effective and efficient in extracting the features. It is also robust to noise. Experimental results using the FVC2002 and Bologna databases show the feasibility of the proposed method..

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Citations
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01 Jan 2010

2,172 citations


Journal ArticleDOI
Abstract: The real-time biometric systems are used to authenticate persons for wide range of security applications. In this paper, we propose implementation of fingerprint-based biometric system using Optimized 5/3 DWT architecture and Modified CORDIC-based Fast Fourier Transform (FFT). The Optimized 2D-DWT architecture is designed using Optimized 1D-DWT architectures, Memory Units and novel Controller Unit which is used to scan rows and columns of an image. The database fingerprint image is applied to the proposed Optimized 2D-DWT architecture to obtain four sub-bands of LL, LH, HL and HH. The efficient architecture of FFT is designed by using Modified CORDIC processor which generates twiddle factor angles of range $$0^{\circ }$$ – $$360^{\circ }$$ using Pre-processing Unit and Comparator Block. Further, the LL sub-band coefficients are applied to the Modified CORDIC based FFT to generate final fingerprint features. The test fingerprint features are obtained by repeating the same procedure and are used to match the database fingerprint image features using Euclidean Distance. The performance parameters of proposed architecture in terms of area utilization, speed and accuracy is compared with existing architecture to validate the obtained results.

8 citations


Proceedings ArticleDOI
10 Sep 2015
TL;DR: This paper proposes FPGA Implementation of Fingerprint Recognition System using Adaptive Threshold Technique with novel adaptive threshold for each person and it is observed that the success rate of identifying a person is high in the proposed method compared to existing techniques.
Abstract: The real time fingerprint biometric system is implemented using FGPA. In this paper, we propose FPGA Implementation of Fingerprint Recognition System using Adaptive Threshold Technique with novel adaptive threshold for each person. The fingerprint images are considered from FVC2004 (DB3_A) and processed to resize fingerprint size to 256X256. The DWT is applied on fingerprint and considered only LL coefficients as features of fingerprint. The Adaptive Threshold value for each person is computed using Deviations between two successive samples of a person, Average Deviation, Standard Deviation and constant. The Adaptive Threshold for test image is computed using Deviations between test images and samples of database, Average Deviation, Standard Deviation and constant. If the Average Threshold of test image is less than Average Threshold of a person then it is considered as match else mismatched. It is observed that the success rate of identifying a person is high in the proposed method compared to existing techniques and also the device utilization in the proposed architecture is less compared to existing architectures.

3 citations


Journal ArticleDOI
TL;DR: An efficient Finite State Machine FSM based reconfigurable architecture for fingerprint recognition using fusion scores with correlation matching technique for FVC2004 DB3 Database is proposed and performance parameters such as TSR Total Success Rate, FAR False Acceptance Rate, and FRR False Rejection Rate are computed.
Abstract: The fingerprint identification is an efficient biometric technique to authenticate human beings in real-time Big Data Analytics. In this paper, we propose an efficient Finite State Machine FSM based reconfigurable architecture for fingerprint recognition. The fingerprint image is resized, and Compound Linear Binary Pattern CLBP is applied on fingerprint, followed by histogram to obtain histogram CLBP features. Discrete Wavelet Transform DWT Level 2 features are obtained by the same methodology. The novel matching score of CLBP is computed using histogram CLBP features of test image and fingerprint images in the database. Similarly, the DWT matching score is computed using DWT features of test image and fingerprint images in the database. Further, the matching scores of CLBP and DWT are fused with arithmetic equation using improvement factor. The performance parameters such as TSR Total Success Rate, FAR False Acceptance Rate, and FRR False Rejection Rate are computed using fusion scores with correlation matching technique for FVC2004 DB3 Database. The proposed fusion based VLSI architecture is synthesized on Virtex xc5vlx30T-3 FPGA board using Finite State Machine resulting in optimized parameters.

2 citations


Cites background from "Multiresolution Feature Based Subsp..."

  • ...The DWT [38] provides spatial and frequency characteristics of an image....

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Proceedings ArticleDOI
19 Jun 2015
TL;DR: Gabor Wavelet Transform based fingerprint recognition system has been realized and experimental results have shown that the proposed method can improve the accuracy of existing methods.
Abstract: A biometric system provides automatic identification of an individual based on a unique feature or characteristic possessed by the individual. Today, fingerprint has a wide field of use in several areas of biometric system. It is especially used in human identification and verification, which is more reliable than the traditional methods used for access. In this work, Gabor Wavelet Transform based fingerprint recognition system has been realized. The wavelet features are extracted from the gray-scale fingerprint image. Finally, the k nearest neighbor classifier is used for the recognition of fingerprint images. The proposed algorithm is tested on images from PolyU high resolution fingerprint database. Experimental results have shown that the proposed method can improve the accuracy of existing methods.

1 citations


References
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Journal ArticleDOI
Abstract: Multiresolution representations are effective for analyzing the information content of images. The properties of the operator which approximates a signal at a given resolution were studied. It is shown that the difference of information between the approximation of a signal at the resolutions 2/sup j+1/ and 2/sup j/ (where j is an integer) can be extracted by decomposing this signal on a wavelet orthonormal basis of L/sup 2/(R/sup n/), the vector space of measurable, square-integrable n-dimensional functions. In L/sup 2/(R), a wavelet orthonormal basis is a family of functions which is built by dilating and translating a unique function psi (x). This decomposition defines an orthogonal multiresolution representation called a wavelet representation. It is computed with a pyramidal algorithm based on convolutions with quadrature mirror filters. Wavelet representation lies between the spatial and Fourier domains. For images, the wavelet representation differentiates several spatial orientations. The application of this representation to data compression in image coding, texture discrimination and fractal analysis is discussed. >

19,033 citations


Journal ArticleDOI
TL;DR: A near-real-time computer system that can locate and track a subject's head, and then recognize the person by comparing characteristics of the face to those of known individuals, and that is easy to implement using a neural network architecture.
Abstract: We have developed a near-real-time computer system that can locate and track a subject's head, and then recognize the person by comparing characteristics of the face to those of known individuals. The computational approach taken in this system is motivated by both physiology and information theory, as well as by the practical requirements of near-real-time performance and accuracy. Our approach treats the face recognition problem as an intrinsically two-dimensional (2-D) recognition problem rather than requiring recovery of three-dimensional geometry, taking advantage of the fact that faces are normally upright and thus may be described by a small set of 2-D characteristic views. The system functions by projecting face images onto a feature space that spans the significant variations among known face images. The significant features are known as "eigenfaces," because they are the eigenvectors (principal components) of the set of faces; they do not necessarily correspond to features such as eyes, ears, and noses. The projection operation characterizes an individual face by a weighted sum of the eigenface features, and so to recognize a particular face it is necessary only to compare these weights to those of known individuals. Some particular advantages of our approach are that it provides for the ability to learn and later recognize new faces in an unsupervised manner, and that it is easy to implement using a neural network architecture.

14,128 citations


"Multiresolution Feature Based Subsp..." refers background or methods in this paper

  • ...University of Bologna database consists of images of 20 subjects with eight images per subject [8]....

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  • ...The arguments a and b denote the scale and translation parameters respectively [8]....

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  • ...The smooth flow pattern of ridges and valleys in a fingerprint can be viewed as an oriented texture field [8]....

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Journal ArticleDOI
TL;DR: A brief overview of the field of biometrics is given and some of its advantages, disadvantages, strengths, limitations, and related privacy concerns are summarized.
Abstract: A wide variety of systems requires reliable personal recognition schemes to either confirm or determine the identity of an individual requesting their services. The purpose of such schemes is to ensure that the rendered services are accessed only by a legitimate user and no one else. Examples of such applications include secure access to buildings, computer systems, laptops, cellular phones, and ATMs. In the absence of robust personal recognition schemes, these systems are vulnerable to the wiles of an impostor. Biometric recognition, or, simply, biometrics, refers to the automatic recognition of individuals based on their physiological and/or behavioral characteristics. By using biometrics, it is possible to confirm or establish an individual's identity based on "who she is", rather than by "what she possesses" (e.g., an ID card) or "what she remembers" (e.g., a password). We give a brief overview of the field of biometrics and summarize some of its advantages, disadvantages, strengths, limitations, and related privacy concerns.

4,384 citations


"Multiresolution Feature Based Subsp..." refers background in this paper

  • ...Because of this, fingerprints are used to authenticate the person [1]....

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01 Jan 2010

2,172 citations


Journal ArticleDOI
TL;DR: A filter-based fingerprint matching algorithm which uses a bank of Gabor filters to capture both local and global details in a fingerprint as a compact fixed length FingerCode and is able to achieve a verification accuracy which is only marginally inferior to the best results of minutiae-based algorithms published in the open literature.
Abstract: Biometrics-based verification, especially fingerprint-based identification, is receiving a lot of attention. There are two major shortcomings of the traditional approaches to fingerprint representation. For a considerable fraction of population, the representations based on explicit detection of complete ridge structures in the fingerprint are difficult to extract automatically. The widely used minutiae-based representation does not utilize a significant component of the rich discriminatory information available in the fingerprints. Local ridge structures cannot be completely characterized by minutiae. Further, minutiae-based matching has difficulty in quickly matching two fingerprint images containing a different number of unregistered minutiae points. The proposed filter-based algorithm uses a bank of Gabor filters to capture both local and global details in a fingerprint as a compact fixed length FingerCode. The fingerprint matching is based on the Euclidean distance between the two corresponding FingerCodes and hence is extremely fast. We are able to achieve a verification accuracy which is only marginally inferior to the best results of minutiae-based algorithms published in the open literature. Our system performs better than a state-of-the-art minutiae-based system when the performance requirement of the application system does not demand a very low false acceptance rate. Finally, we show that the matching performance can be improved by combining the decisions of the matchers based on complementary (minutiae-based and filter-based) fingerprint information.

1,180 citations


"Multiresolution Feature Based Subsp..." refers background in this paper

  • ...A point of the most curvature in a fingerprint image has been detected and considered as a reference point as proposed in [2]....

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