Hierarchical fusion for matching simultaneous latent fingerprint
06 Dec 2012-pp 377-382
TL;DR: An automated hierarchical fusion approach is proposed for fusing evidences from multiple latent impressions and IIITD simultaneous latent fingerprint database is prepared to drive further research in this area.
Abstract: Simultaneous latent fingerprints are a cluster of latent fingerprints that are concurrently deposited by the same person. Inherent challenges of latent fingerprints such as partial and smudgy ridge flow information, presence of background noise, and availability of less number of features makes it challenging to develop an automated system for simultaneous latent fingerprint matching. This research attempts to fill this gap by developing a fusion framework. The contribution of this paper is two-fold: (i) an automated hierarchical fusion approach is proposed for fusing evidences from multiple latent impressions and (ii) IIITD simultaneous latent fingerprint database is prepared to drive further research in this area. The proposed algorithm yields promising results on the simultaneous latent fingerprint database.
Citations
More filters
TL;DR: This paper highlights the importance of the overlapped fingerprint segmentation (ROI extraction) process, a step for which there are no automatic techniques yet, and explains the main concepts and surveys the literature in the field.
Abstract: Fingerprint matching is a widely used process to aid in crime scene investigation, where fingerprint fragments are often found on objects and surfaces. In such cases, the lifted fingerprints (called latents) are usually of poor quality and often appear overlapped and against a noisy background. These aspects make latent fingerprint --- especially overlapped latent fingerprints --- segmentation and enhancement (for subsequent matching) a difficult problem, for which several solutions have been proposed during the past few years. This paper presents an overview of contemporary techniques for overlapped fingerprint separation in the context of latent overlapped fingerprint matching. In addition to explaining the main concepts and surveying the literature in the field, it highlights the importance of the overlapped fingerprint segmentation (ROI extraction) process, a step for which there are no automatic techniques yet.
19 citations
Cites background from "Hierarchical fusion for matching si..."
...IIIT-D Simultaneous Latent Fingerprint (SLF)c [44] 1080 Consists of latent fingerprints of 15 subjects and their mated optical slap fingerprints....
[...]
TL;DR: This article proposes a patch-based technique for segmentation of latent fingerprint images, which uses Convolutional Neural Network (CNN) to classify patches and an ROI is constructed to mark out the foreground from the background of latent fingerprints images.
Abstract: Latent fingerprint segmentation involves marking out all the foreground regions accurately in a latent fingerprint image, but due to poor quality images and complex background, segmentation of latent fingerprint images is one of the most difficult tasks in automatic latent fingerprint recognition systems. In this article, we propose a patch-based technique for segmentation of latent fingerprint images, which uses Convolutional Neural Network (CNN) to classify patches. CNN has recently shown impressive performance in the field of pattern recognition, classification, and object detection, which inspired us to use CNN for this complex task. We trained the CNN model using SGD to classify image patches into fingerprint and non-fingerprint classes followed by proposed false patch removal technique, which uses “majority of neighbors” to remove the isolated and miss-classified patches. Finally, based on the final class of patches, an ROI is constructed to mark out the foreground from the background of lat...
15 citations
Cites methods from "Hierarchical fusion for matching si..."
...The database has been published by the Image Analysis and Biometrics Lab Indraprastha Institute of Information Technology, Delhi (Sankaran, Vatsa, and Singh 2012)....
[...]
01 Nov 2016
TL;DR: This paper surveys the Available fingerprint acquisition technologies and the available fingerprint databases and identifies the advantages and disadvantages of each technology and database.
Abstract: Since security vulnerabilities represent one of the grand challenges of the Internet of Things (IoT), researchers have proposed what is known as the Internet of Biometric Things (IoBT), which mixes traditional biometric technologies with context-aware authentication techniques. One of the most famous biometric technologies is electronic fingerprint recognition, which acquire fingerprints using different technologies, some of which are more suitable for IoBT than others. Moreover, different fingerprint databases have been built to study the impact of different factors on the accuracy of different fingerprint recognition algorithms and systems. In this paper, we survey the available fingerprint acquisition technologies and the available fingerprint databases. We also identify the advantages and disadvantages of each technology and database.
13 citations
TL;DR: Different accessible strategies and methods that have been utilized as a part of the past exploration concentrates on furthermore gives the bearing to further research in the different field of inactive unique finger impression application.
Abstract: Latent fingerprint has become more popular and attracted among the researchers in the recent days and it has been used widely in security such as India’s Aadhaar project, Department of Homeland Security’s US-VISIT program, the UK Border Agency, law enforcement and forensic applications. There have been different biometric traits that were used for matching to identify the person. While investigation a small number of accesses are recognized in latent fingerprint images because the fingerprint has own individuality. Latent fingerprint has been consisting some challenges in term of poor quality images, unclear texture and nonlinear distortion, appropriate matching algorithm and publicly available latent fingerprint database. Consequently, the study has considered and talked about different accessible strategies and methods that have been utilized as a part of the past exploration concentrates on furthermore gives the bearing to further research in the different field of inactive unique finger impres...
9 citations
Cites methods from "Hierarchical fusion for matching si..."
...IIIT-D SLF (Simultaneous Latent Fingerprint) [30] database contains 1080 images with mated slap 500 PPI exemplars, 2 sessions of SLF are lifted using block powder dusting....
[...]
...ELFT (Evaluation of Latent Fingerprint Technologies) - EFS (Extended Feature Set) [2] contains 1100 image which has been scanned at 500PPI and 1000 PPI as a gray – scale images....
[...]
TL;DR: Level 3 features, particularly pores are extracted using Fully Convolution Neural Network (FCN) from the collected latent fingerprints using the RUVIS, which plays a significant role in matching these latent impressions with plain impressions.
8 citations
References
More filters
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
01 Dec 2003
TL;DR: The main purpose has been to consider a large scale population, with statistical significance, in a real multimodal procedure, and including several sources of variability that can be found in real environments.
Abstract: The current need for large multimodal databases to evaluate automatic biometric recognition systems has motivated the development of the MCYT bimodal database. The main purpose has been to consider a large scale population, with statistical significance, in a real multimodal procedure, and including several sources of variability that can be found in real environments. The acquisition process, contents and availability of the single-session baseline corpus are fully described. Some experiments showing consistency of data through the different acquisition sites and assessing data quality are also presented.
676 citations
"Hierarchical fusion for matching si..." refers background in this paper
...To make the latent matching environment more challenging and realistic, 2000 optical fingerprints pertaining to 100 subjects from the MCYT database [13] are added to the gallery....
[...]
TL;DR: Experiments on three multibiometric databases indicate that the proposed fusion framework achieves consistently high performance compared to commonly used score fusion techniques based on score transformation and classification.
Abstract: Multibiometric systems fuse information from different sources to compensate for the limitations in performance of individual matchers. We propose a framework for the optimal combination of match scores that is based on the likelihood ratio test. The distributions of genuine and impostor match scores are modeled as finite Gaussian mixture model. The proposed fusion approach is general in its ability to handle 1) discrete values in biometric match score distributions, 2) arbitrary scales and distributions of match scores, 3) correlation between the scores of multiple matchers, and 4) sample quality of multiple biometric sources. Experiments on three multibiometric databases indicate that the proposed fusion framework achieves consistently high performance compared to commonly used score fusion techniques based on score transformation and classification.
538 citations
"Hierarchical fusion for matching si..." refers methods in this paper
...In this research, we have used (1) weighted sum rule [7] and (2) product of likelihood ratio (PLR) fusion [12]....
[...]
...The fused score for Algorithmj is computed using the weighted PLR fusion [12] as shown in equation 2....
[...]
Book•
27 Oct 1999
TL;DR: In this paper, the first step toward qualitative analysis of ridgeology has been taken towards a qualitative analysis in the field of Ridgeology, and the identification process of ridge identification has been described.
Abstract: Preface Introduction The First Step Toward Quantitative-Qualitative Analysis Ridgeology Revolution History of Friction Ridge Identification Primitive Knowledge Early Pioneers Scientific Researchers The Friction Ridge Medium Structure of Friction Skin Growth of Friction Skin The Identification Process Premises of Friction Ridge Identification Philosophy of Friction Ridge Identification Human Sight Methodology of Friction Ridge Identification Friction Ridge Analysis Friction Ridge Comparison Friction Ridge Evaluation Verification Poroscopy And Edgeoscopy Poroscopy Edgeoscopy Friction Ridge Analysis Report Ridgeology Study Key An Introduction To Palmar Flexion Crease Identification The Beginning Bibliography Glossary
377 citations
"Hierarchical fusion for matching si..." refers methods in this paper
...Simultaneous latent fingerprint examination is a complex application of ACE-V, where establishing simultaneity and utilizing multiple latent prints are main steps....
[...]
TL;DR: The experimental results indicate that singularity, ridge quality map, and ridge flow map are the most effective features in improving the matching accuracy.
Abstract: Latent fingerprint identification is of critical importance to law enforcement agencies in identifying suspects: Latent fingerprints are inadvertent impressions left by fingers on surfaces of objects. While tremendous progress has been made in plain and rolled fingerprint matching, latent fingerprint matching continues to be a difficult problem. Poor quality of ridge impressions, small finger area, and large nonlinear distortion are the main difficulties in latent fingerprint matching compared to plain or rolled fingerprint matching. We propose a system for matching latent fingerprints found at crime scenes to rolled fingerprints enrolled in law enforcement databases. In addition to minutiae, we also use extended features, including singularity, ridge quality map, ridge flow map, ridge wavelength map, and skeleton. We tested our system by matching 258 latents in the NIST SD27 database against a background database of 29,257 rolled fingerprints obtained by combining the NIST SD4, SD14, and SD27 databases. The minutiae-based baseline rank-1 identification rate of 34.9 percent was improved to 74 percent when extended features were used. In order to evaluate the relative importance of each extended feature, these features were incrementally used in the order of their cost in marking by latent experts. The experimental results indicate that singularity, ridge quality map, and ridge flow map are the most effective features in improving the matching accuracy.
292 citations
"Hierarchical fusion for matching si..." refers background or methods in this paper
...Jain and Feng [11] provided a comprehensive analysis of latent fingerprint matching....
[...]
...Dusted latent fingerprints are usually lifted from the surface using tapes, stored in cards, and scanned using optical scanners....
[...]