On analysis of rural and urban indian fingerprint images
04 Jan 2010-pp 55-61
TL;DR: The analysis shows that rural population is very challenging and existing algorithms/systems are unable to provide acceptable performance and fingerprint recognition algorithms provide comparatively better performance on urban population.
Abstract: This paper presents a feasibility study to compare the performance of fingerprint recognition on rural and urban Indian population. The analysis shows that rural population is very challenging and existing algorithms/systems are unable to provide acceptable performance. On the other hand, fingerprint recognition algorithms provide comparatively better performance on urban population. The study also shows that poor images quality, worn and damaged patterns and some special characteristics affect the performance of fingerprint recognition.
Citations
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02 May 2014
TL;DR: In this paper simulations with a few fingerprint databases containing multiple fingerprint images from every finger are conducted and effects of minutia quality and threshold on matching are discussed.
Abstract: Fingerprint is a biometric not only widely used in forensic investigation, but also in civil applications for user access control. At a crime scene an investigator may find fingerprints inadvertently left by a suspect. Even though fingerprints of this kind can be very useful for finding the perpetrator, recent years have seen multiple cases of misidentification caused by partial or latent fingerprints. Question about the usefulness of fingerprints in courtroom is raised due to these incidents. In civil applications a fingerprint identification system requires a user to present a live finger for image capturing at registration. Upon recognition new images from the same finger are captured, processed, and then matched against the registered template. During the processes, how often would this user be positively identified with the newly acquired images? In this paper we conduct simulations with a few fingerprint databases containing multiple fingerprint images from every finger and report our findings. Effects of minutia quality and threshold on matching are also discussed in this paper.
Cites methods from "On analysis of rural and urban indi..."
...Experiments were carried out with the following fingerprint databases: IIT rural database [25], databases 3A and 4A from FVC2006 [26], and CASIA Fingerprint-v5 [27]....
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TL;DR: Zhang et al. as discussed by the authors proposed a context-aware GAN (CA-GAN) to learn spatial context by ensuring that the model not only performs fingerprint restoration but also accurately predicts the correct spatial arrangement of randomly arranged fingerprint patches.
Abstract: The literature on fingerprint restoration algorithms firmly advocates exploiting contextual information, such as ridge orientation field, ridge spacing, and ridge frequency, to recover ridge details in fingerprint regions with poor quality ridge structure. However, most state-of-the-art convolutional neural network based fingerprint restoration models exploit spatial context only through convolution operations. Motivated by this observation, this article introduces a novel context-aware fingerprint restoration model: context-aware GAN (CA-GAN). CA-GAN is explicitly regularized to learn spatial context by ensuring that the model not only performs fingerprint restoration but also accurately predicts the correct spatial arrangement of randomly arranged fingerprint patches. Experimental results establish better fingerprint restoration ability of CA-GAN compared to the state-of-the-art.
01 Dec 2014
TL;DR: Extensive simulation is carried out in MATLAB environment to show the superiority of the proposed feature extraction technique over state of art.
Abstract: Automated Fingerprint Identification Systems (AFIS) currently rely only on Level 1 and Level 2 features. But these features are not much helpful for forensic experts as the experiment deals with partial to full print matching of latent fingerprint. Forensic experts takes the advantage of extended feature proposed by "Committee to Define an Extended Fingerprint Feature Set" (CDEFFS). This paper presents extraction technique of two extended features, dots and incipient ridges by tracing valleys. We have found starting points on the valley by analyzing the frequencies present in the fingerprint. Valley are traced from the starting point using first marching method (FMM). An intensity checking method is used for finding these feature points. Then matching are done by establishing spatial relation with minutiae using Delaunay triangulation. Extensive simulation is carried out in MATLAB environment to show the superiority of the proposed feature extraction technique over state of art. Accuracy of the proposed feature extraction scheme also has been shown using special database 30 and IIIT Delhi database.
Cites methods from "On analysis of rural and urban indi..."
...Similarly, in case of Rural Indian Fingerprint Database, the first image is divided into 12 non-overlapping block of size 150x 150 and rest pixels are discarded at boundary....
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...We have used NIST special database 30 (SD30) [12] and Rural Indian Fingerprint Database [7] of lIlT Delhi for performance evaluation....
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01 Jan 2021
TL;DR: This chapter proposes two contributions: a pore detection method for high-resolution fingerprint image based on the morphological operation (skeletonization) and the labeled connect component method, and a new method to match pores without an alignment.
Abstract: Nowadays one of the most popular topics in fingerprint recognition academic research is the high-resolution fingerprint identification way. This technique has been prominently attractive to the worldwide scientific community thanks to the possibility of using level 3 features like pores which cannot be detected in lower resolution images. In this context, this chapter proposes two contributions: First, a pore detection method for high-resolution fingerprint image based on the morphological operation (skeletonization) and the labeled connect component method. Second, a new method to match pores without an alignment. Our matching approach is based on the contextual characteristics of the pore. It consists of positions and orientations of pore neighbors, which are defined as polar coordinates given in the polar system centered on the considered pore. The proposed algorithms are tested on a high-resolution fingerprint database. Experimental results show that our methods outperform the existing algorithms.
Posted Content•
TL;DR: In this article, the authors proposed a data uncertainty-based framework which enables the state-of-the-art fingerprint preprocessing models to quantify noise present in the input image and identify fingerprint regions with background noise and poor ridge clarity.
Abstract: The effectiveness of fingerprint-based authentication systems on good quality fingerprints is established long back. However, the performance of standard fingerprint matching systems on noisy and poor quality fingerprints is far from satisfactory. Towards this, we propose a data uncertainty-based framework which enables the state-of-the-art fingerprint preprocessing models to quantify noise present in the input image and identify fingerprint regions with background noise and poor ridge clarity. Quantification of noise helps the model two folds: firstly, it makes the objective function adaptive to the noise in a particular input fingerprint and consequently, helps to achieve robust performance on noisy and distorted fingerprint regions. Secondly, it provides a noise variance map which indicates noisy pixels in the input fingerprint image. The predicted noise variance map enables the end-users to understand erroneous predictions due to noise present in the input image. Extensive experimental evaluation on 13 publicly available fingerprint databases, across different architectural choices and two fingerprint processing tasks demonstrate effectiveness of the proposed framework.
References
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Book•
10 Mar 2005TL;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
"On analysis of rural and urban indi..." refers background in this paper
...Fingerprints are considered reliable to identify individuals and are used in both biometric and forensic applications [1]....
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TL;DR: An improved version of the minutia extraction algorithm proposed by Ratha et al. (1995), which is much faster and more reliable, is implemented for extracting features from an input fingerprint image captured with an online inkless scanner and an alignment-based elastic matching algorithm has been developed.
Abstract: Fingerprint verification is one of the most reliable personal identification methods. However, manual fingerprint verification is incapable of meeting today's increasing performance requirements. An automatic fingerprint identification system (AFIS) is needed. This paper describes the design and implementation of an online fingerprint verification system which operates in two stages: minutia extraction and minutia matching. An improved version of the minutia extraction algorithm proposed by Ratha et al. (1995), which is much faster and more reliable, is implemented for extracting features from an input fingerprint image captured with an online inkless scanner. For minutia matching, an alignment-based elastic matching algorithm has been developed. This algorithm is capable of finding the correspondences between minutiae in the input image and the stored template without resorting to exhaustive search and has the ability of adaptively compensating for the nonlinear deformations and inexact pose transformations between fingerprints. The system has been tested on two sets of fingerprint images captured with inkless scanners. The verification accuracy is found to be acceptable. Typically, a complete fingerprint verification procedure takes, on an average, about eight seconds on a SPARC 20 workstation. These experimental results show that our system meets the response time requirements of online verification with high accuracy.
1,376 citations
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
"On analysis of rural and urban indi..." refers methods in this paper
...– Implementation of minutiae feature extraction and matching [2] termed as Algorithm - A – Implementation of filterbank based feature extraction and matching [3] termed as Algorithm - B – Two commercial fingerprint recognition systems, termed as System - C and System - D(1)...
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TL;DR: In this article, a filter bank based fingerprint representation is implemented and the overall performance of the developed system is tested and the results have shown that this system can be used effectively for secure online verification applications.
Abstract: As organizations search for more secure authentication methods for user access, e-commerce, and other security applications, biometrics is gaining increasing attention. With an increasing emphasis on the emerging automatic personal identification applications, fingerprint based identification is becoming more popular. The most widely used fingerprint representation is the minutiae based representation. The main drawback with this representation is that it does not utilize a significant component of the rich discriminatory information available in the fingerprints. Local ridge structures cannot be completely characterized by minutiae. Also, it is difficult quickly to match two fingerprint images containing different number of unregistered minutiae points. In this study filter bank based representation, which eliminates these weakness, is implemented and the overall performance of the developed system is tested. The results have shown that this system can be used effectively for secure online verification applications.
69 citations
TL;DR: A novel online fingerprint verification algorithm and distribution system that is insensitive to fingerprint image distortion, scale, and rotation, and robust even on poor quality fingerprint images is proposed.
Abstract: In this paper, a novel online fingerprint verification algorithm and distribution system is proposed. In the beginning, fingerprint acquisition, image preprocessing, and feature extraction are conducted on workstations. Then, the extracted feature is transmitted over the internet. Finally, fingerprint verification is processed on a server through web-based database query. For the fingerprint feature extraction, a template is imposed on the fingerprint image to calculate the type and direction of minutiae. A data structure of the feature set is designed in order to accurately match minutiae features between the testing fingerprint and the references in the database. An elastic structural feature matching algorithm is employed for feature verification. The proposed fingerprint matching algorithm is insensitive to fingerprint image distortion, scale, and rotation. Experimental results demonstrated that the matching algorithm is robust even on poor quality fingerprint images. Clients can remotely use ADO.NET on their workstations to verify the testing fingerprint and manipulate fingerprint feature database on the server through the internet. The proposed system performed well on benchmark fingerprint dataset.
7 citations
"On analysis of rural and urban indi..." refers methods in this paper
...– Implementation of minutiae feature extraction and matching [2] termed as Algorithm - A – Implementation of filterbank based feature extraction and matching [3] termed as Algorithm - B – Two commercial fingerprint recognition systems, termed as System - C and System - D(1)...
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