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Journal ArticleDOI

Enhancement of feature extraction for low-quality fingerprint images using stochastic resonance

01 Jan 2011-Pattern Recognition Letters (North-Holland)-Vol. 32, Iss: 2, pp 107-113
TL;DR: Experimental results show that Gaussian noise added to low-quality fingerprint images enables the extraction of useful features for biometric identification by adding noise to the original signal.
About: This article is published in Pattern Recognition Letters.The article was published on 2011-01-01. It has received 69 citations till now. The article focuses on the topics: Fingerprint Verification Competition & Feature extraction.
Citations
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TL;DR: This paper presents a review of a large number of techniques present in the literature for extracting fingerprint minutiae, broadly classified as those working on binarized images and those that work on gray scale images directly.
Abstract: Fingerprints are the oldest and most widely used form of biometric identification. Everyone is known to have unique, immutable fingerprints. As most Automatic Fingerprint Recognition Systems are based on local ridge features known as minutiae, marking minutiae accurately and rejecting false ones is very important. However, fingerprint images get degraded and corrupted due to variations in skin and impression conditions. Thus, image enhancement techniques are employed prior to minutiae extraction. A critical step in automatic fingerprint matching is to reliably extract minutiae from the input fingerprint images. This paper presents a review of a large number of techniques present in the literature for extracting fingerprint minutiae. The techniques are broadly classified as those working on binarized images and those that work on gray scale images directly.

102 citations


Cites background from "Enhancement of feature extraction f..."

  • ...Choonwoo et al [41] presented a novel approach to enhance feature extraction for low quality fingerprint images using stochastic resonance (SR)....

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Journal ArticleDOI
TL;DR: The internal noise of an image has been utilised to produce a noise-induced transition of a dark image from a state of low contrast to that of high contrast.
Abstract: In this study, a dynamic stochastic resonance (DSR)-based technique in spatial domain has been proposed for the enhancement of dark- and low-contrast images. Stochastic resonance (SR) is a phenomenon in which the performance of a system (low-contrast image) can be improved by addition of noise. However, in the proposed work, the internal noise of an image has been utilised to produce a noise-induced transition of a dark image from a state of low contrast to that of high contrast. DSR is applied in an iterative fashion by correlating the bistable system parameters of a double-well potential with the intensity values of a low-contrast image. Optimum output is ensured by adaptive computation of performance metrics - relative contrast enhancement factor ( F ), perceptual quality measures and colour enhancement factor. When compared with the existing enhancement techniques such as adaptive histogram equalisation, gamma correction, single-scale retinex, multi-scale retinex, modified high-pass filtering, edge-preserving multi-scale decomposition and automatic controls of popular imaging tools, the proposed technique gives significant performance in terms of contrast and colour enhancement as well as perceptual quality. Comparison with a spatial domain SR-based technique has also been illustrated.

88 citations

Journal ArticleDOI
13 Aug 2014
TL;DR: This paper presents a systematic noise-enhanced information processing framework to analyze and optimize the performance of engineered systems and discusses the constructive effect of noise in associative memory recall.
Abstract: Noise, traditionally defined as an unwanted signal or disturbance, has been shown to play an important constructive role in many information processing systems and algorithms. This noise enhancement has been observed and employed in many physical, biological, and engineered systems. Indeed stochastic facilitation (SF) has been found critical for certain biological information functions such as detection of weak, subthreshold stimuli or suprathreshold signals through both experimental verification and analytical model simulations. In this paper, we present a systematic noise-enhanced information processing framework to analyze and optimize the performance of engineered systems. System performance is evaluated not only in terms of signal-to-noise ratio but also in terms of other more relevant metrics such as probability of error for signal detection or mean square error for parameter estimation. As an important new instance of SF, we also discuss the constructive effect of noise in associative memory recall. Potential enhancement of image processing systems via the addition of noise is discussed with important applications in biomedical image enhancement, image denoising, and classification.

66 citations

Journal ArticleDOI
TL;DR: The proposed DSR-SVD technique is found to give noteworthy better performance in terms of contrast enhancement factor, color enhancement factor and perceptual quality measure.
Abstract: In this paper, a dynamic stochastic resonance (DSR)-based technique in singular value domain for contrast enhancement of dark images has been presented. The internal noise due to the lack of illumination is utilized using a DSR iterative process to obtain enhancement in contrast, colorfulness as well as perceptual quality. DSR is a phenomenon that has been strategically induced and exploited and has been found to give remarkable response when applied on the singular values of a dark low-contrast image. When an image is represented as a summation of image layers comprising of eigen vectors and values, the singular values denote luminance information of each such image layer. By application of DSR on the singular values using the analogy of a bistable double-well potential model, each of the singular values is scaled to produce an image with enhanced contrast as well as visual quality. When compared with performance of some existing spatial domain enhancement techniques, the proposed DSR-SVD technique is found to give noteworthy better performance in terms of contrast enhancement factor, color enhancement factor and perceptual quality measure.

59 citations

01 Jan 2010
TL;DR: This paper presents a systematic analysis of a variety of different ad hoc network topologies in terms of node placement, node mobility and routing protocols through several simulated scenarios.
Abstract: In this paper we examine the behavior of Ad Hoc networks through simulations, using different routing protocols and various topologies. We examine the difference in performance, using CBR application, with packets of different size through a variety of topologies, showing the impact node placement has on networks performance. We show that the choice of routing protocol plays an important role on network’s performance. We also quantify node mobility effects, by looking into both static and fully mobile configurations. Our paper presents a systematic analysis of a variety of different ad hoc network topologies in terms of node placement, node mobility and routing protocols through several simulated scenarios.

58 citations

References
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Book
10 Mar 2005
TL;DR: This unique reference work is an absolutely essential resource for all biometric security professionals, researchers, and systems administrators.
Abstract: A major new professional reference work on fingerprint security systems and technology from leading international researchers in the field Handbook provides authoritative and comprehensive coverage of all major topics, concepts, and methods for fingerprint security systems This unique reference work is an absolutely essential resource for all biometric security professionals, researchers, and systems administrators

3,821 citations


"Enhancement of feature extraction f..." refers background in this paper

  • ...Most commercially available fingerprint recognition systems depend on reliable extraction of feature points from fingerprint images for matching with reference features (Maltoni et al., 2003)....

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Book
01 Jan 2008
TL;DR: In this article, a theoretical approach based on linear response theory (LRT) is described, and two new forms of stochastic resonance, predicted on the basis of LRT and subsequently observed in analogue electronic experiments, are described.
Abstract: Stochastic resonance (SR) - a counter-intuitive phenomenon in which the signal due to a weak periodic force in a nonlinear system can be {\it enhanced} by the addition of external noise - is reviewed A theoretical approach based on linear response theory (LRT) is described It is pointed out that, although the LRT theory of SR is by definition restricted to the small signal limit, it possesses substantial advantages in terms of simplicity, generality and predictive power The application of LRT to overdamped motion in a bistable potential, the most commonly studied form of SR, is outlined Two new forms of SR, predicted on the basis of LRT and subsequently observed in analogue electronic experiments, are described

2,403 citations

Journal ArticleDOI
TL;DR: A fast fingerprint enhancement algorithm is presented, which can adaptively improve the clarity of ridge and valley structures of input fingerprint images based on the estimated local ridge orientation and frequency.
Abstract: In order to ensure that the performance of an automatic fingerprint identification/verification system will be robust with respect to the quality of input fingerprint images, it is essential to incorporate a fingerprint enhancement algorithm in the minutiae extraction module. We present a fast fingerprint enhancement algorithm, which can adaptively improve the clarity of ridge and valley structures of input fingerprint images based on the estimated local ridge orientation and frequency. We have evaluated the performance of the image enhancement algorithm using the goodness index of the extracted minutiae and the accuracy of an online fingerprint verification system. Experimental results show that incorporating the enhancement algorithm improves both the goodness index and the verification accuracy.

2,212 citations


"Enhancement of feature extraction f..." refers background or methods in this paper

  • ...The Gabor filter has been the most popular approach to enhance fingerprint ridge and valley patterns in gray level (Hong et al., 1998)....

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  • ...Most fingerprint recognition systems utilize minutiae points as features such as the location and angle information of ridge endings and bifurcations (Hong et al., 1998)....

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  • ...Fingerprint enhancement techniques are often based on local ridge directional binarization (Ratha et al., 1995), Gabor filter (Hong et al., 1998), short-time Fourier transform (Chikkerur et al., 2007), and the wavelet transform (Hsieh et al., 2003)....

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Journal ArticleDOI
05 Jan 1995-Nature
TL;DR: In certain nonlinear systems, including electronic circuits and biological sensory apparatus, the presence of noise can in fact enhance the detection of weak signals, called stochastic resonance.
Abstract: Noise in dynamical systems is usually considered a nuisance. But in certain nonlinear systems, including electronic circuits and biological sensory apparatus, the presence of noise can in fact enhance the detection of weak signals. This phenomenon, called stochastic resonance, may find useful application in physical, technological and biomedical contexts.

1,588 citations


"Enhancement of feature extraction f..." refers background in this paper

  • ...Fingerprint verification has been widely accepted as a key biometric identification technique in commercial and law enforcement applications....

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  • ...SR was first introduced to explain the periodicity of the Earth’s ice-ages (Wiesenfeld and Moss, 1995)....

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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.

1,207 citations


"Enhancement of feature extraction f..." refers methods in this paper

  • ...Other feature extraction approaches use texture information of the fingerprint in order to overcome the sensitiveness of ridge pattern quality (Jain et al., 2000)....

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