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.
Abstract: The 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..
Citations
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TL;DR: In this article, the authors proposed implementation of fingerprint-based biometric system using Optimized 5/3 DWT architecture and Modified CORDIC-based Fast Fourier Transform (FFT).
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.
14 citations
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
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.
3 citations
Cites background from "Multiresolution Feature Based Subsp..."
...The DWT [38] provides spatial and frequency characteristics of an image....
[...]
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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11 Aug 2002
TL;DR: The FVC 2002 database, the test protocol and the main differences between FVC2000 and FVC2002 are discussed.
Abstract: Two years after the first edition, a new Fingerprint Verification Competition (FVC2002) was organized by the authors, with the aim of determining the state-of-the-art in this challenging pattern recognition application. The experience and the feedback received from FVC2000 allowed the authors to improve the organization of FVC2002 and to capture the attention of a significantly higher number of academic and commercial organizations (33 algorithms were submitted). This paper discusses the FVC2002 database, the test protocol and the main differences between FVC2000 and FVC2002. The algorithm performance evaluation will be presented at the 16/sup th/ ICPR.
677 citations
TL;DR: A reliable method for extracting structural features from fingerprint images is presented and a “goodness index” (GI) which compares the results of automatic extraction with manually extracted ground truth is evaluated.
635 citations
TL;DR: A hybrid fingerprint matching scheme that uses both minutiae and ridge flow information to represent and match fingerprints, where the entire image is taken into account while constructing the ridge feature map.
372 citations
11 Aug 2002
TL;DR: A hybrid fingerprint matching scheme that uses both minutiae and ridge flow information to represent and match fingerprints, and the genuine accept rate of the hybrid matcher is observed to be /spl sim/10% higher than that of aminutiae-based matcher at low false accept rates.
Abstract: We describe a hybrid fingerprint matching scheme that uses both minutiae and ridge flow information to represent and match fingerprints. A set of 8 Gabor filters, whose spatial frequencies correspond to the average inter-ridge spacing in fingerprints, is used to capture the ridge strength at equally spaced orientations. A square tessellation of the filtered images is then used to construct an eight-dimensional feature map, called the. ridge feature map. The ridge feature map along with the minutiae set of a fingerprint image is used for matching purposes. The genuine accept rate of the hybrid matcher is observed to be /spl sim/10% higher than that of a minutiae-based matcher at low false accept rates. Fingerprint verification using the hybrid matcher on a Pentium III (800 MHz) processor takes /spl sim/1.4 seconds.
259 citations
"Multiresolution Feature Based Subsp..." refers background in this paper
...The Most of textural images contain a limited range of spatial frequencies, and mutually distinct textures differ significantly in their dominant frequencies [7]...
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...There are at most 1 M eigenfaces with non-zero eigenvalues [7]....
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TL;DR: In this article, an approach to the solution of signal-to-symbol transformation in the domain of flow fields, such as oriented texture fields and velocity vector fields, is discussed.
Abstract: An approach to the solution of signal-to-symbol transformation in the domain of flow fields, such as oriented texture fields and velocity vector fields, is discussed. The authors use the geometric theory of differential equations to derive a symbol set based on the visual appearance of phase portraits which are a geometric representation of the solution curves of a system of differential equations. They also provide the computational framework to start with a given flow field and derive its symbolic representation. Specifically, they segment the given texture, derive its symbolic representation, and perform a quantitative reconstruction of the salient features of the original texture based on the symbolic descriptors. Results of applying this technique to several real texture images are presented. This technique is useful in describing complex flow visualization pictures, defects in lumber processing, defects in semiconductor wafer inspection, and optical flow fields. >
211 citations