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: The results proved that the used software functioned perfectly until a compression ratio of (30–40%) of the raw images; any higher ratio would negatively affect the accuracy of the used system.
Abstract: Despite the large body of work on fingerprint identification systems, most of it focused on using specialized devices. Due to the high price of such devices, some researchers directed their attention to digital cameras as an alternative source for fingerprints images. However, such sources introduce new challenges related to image quality. Specifically, most digital cameras compress captured images before storing them leading to potential losses of information. This study comes to address the need to determine the optimum ratio of the fingerprint image compression to ensure the fingerprint identification system’s high accuracy. This study is conducted using a large in-house dataset of raw images. Therefore, all fingerprint information is stored in order to determine the compression ratio accurately. The results proved that the used software functioned perfectly until a compression ratio of (30–40%) of the raw images; any higher ratio would negatively affect the accuracy of the used system.
154 citations
Cites methods from "Hierarchical fusion for matching si..."
...DB5 1600 100 users x 2 hands x 2 sessions x 4 instances Users left their fingerprints (multifingerprints) on a ceramic tile and then these latent fingerprints were captured using a USB programmable UEye camera and the setup in [48] after a black powder dusting process [29]....
[...]
TL;DR: The process of automatic latent fingerprint matching is divided into five definite stages, and the existing algorithms, limitations, and future research directions in each of the stages are discussed.
Abstract: Latent fingerprint has been used as evidence in the court of law for over 100 years. However, even today, a completely automated latent fingerprint system has not been achieved. Researchers have identified several important challenges in latent fingerprint recognition: 1) low information content; 2) presence of background noise and nonlinear ridge distortion; 3) need for an established scientific procedure for matching latent fingerprints; and 4) lack of publicly available latent fingerprint databases. The process of automatic latent fingerprint matching is divided into five definite stages, and this paper discusses the existing algorithms, limitations, and future research directions in each of the stages.
72 citations
Cites methods from "Hierarchical fusion for matching si..."
...There are three publicly available latent fingerprint databases namely: NIST SD-27 [16] database, IIIT-D latent fingerprint database [78], and IIIT-D SLF database [80]....
[...]
...[80] created a publicly available database for simultaneous latent fingerprint matching called IIITD-SLF database having almost 360 simultaneous impressions from 60 classes....
[...]
TL;DR: This paper presents the multisensor optical and latent fingerprint database of more than 19000 fingerprint images with different intraclass variations during fingerprint capture, and showcases the baseline results of various matching experiments on this database.
Abstract: Large-scale fingerprint recognition involves capturing ridge patterns at different time intervals using various methods, such as live-scan and paper-ink approaches, introducing intraclass variations in the fingerprint. The performance of existing algorithms is significantly affected when fingerprints are captured with diverse acquisition settings such as multisession, multispectral, multiresolution, with slap, and with latent fingerprints. One of the primary challenges in developing a generic and robust fingerprint matching algorithm is the limited availability of large data sets that capture such intraclass diversity. In this paper, we present the multisensor optical and latent fingerprint database of more than 19000 fingerprint images with different intraclass variations during fingerprint capture. We also showcase the baseline results of various matching experiments on this database. The database is aimed to drive research in building robust algorithms toward solving the problem of latent fingerprint matching and handling intraclass variations in fingerprint capture. Some potential applications for this database are identified and the research challenges that can be addressed using this database are also discussed.
67 citations
Cites background or methods from "Hierarchical fusion for matching si..."
...• Simultaneous Latent Fingerprint Matching: The DB5 subset can be used for matching simultaneous latent fingerprints [9], [35]....
[...]
...version of the setup created during the capture of the IIIT-D SLF database [9]....
[...]
...In the same context, simultaneous latent fingerprints are defined as two or more latent fingerprints of the same hand deposited concurrently on the same surface [9]....
[...]
TL;DR: This research focuses on automatically segmenting latent fingerprints to distinguish between ridge and non-ridge patterns, and proposes a novel SIVV based metric to measure the effect of the segmentation algorithm without the requirement to perform the entire matching process.
56 citations
Cites background or methods from "Hierarchical fusion for matching si..."
...• IIIT-D Simultaneous Latent Fingerprint (SLF) database [16] has 1080 latent impressions from 30 subjects (all 10 fingers) with mated exemplar prints....
[...]
...• The performance of the proposed algorithm is evaluated using two different databases: (1) NIST SD-27 database [2] and (2) IIIT-D Combined Latent Fingerprint (CLF) database, which is a combination of IIIT-D latent fingerprint database [15] and IIIT-D SLF database [16]....
[...]
TL;DR: This paper introduces and applies a protocol that evaluates minutia descriptors for latent fingerprint identification in terms of the identification rate plotted in the cumulative match characteristic (CMC) curve, and finds that all the evaluated minutian descriptors obtained identification rates lower than 10% for Rank−1 and 24% forRank−100 comparing the minutiae in the database NIST SD27.
Abstract: Latent fingerprint identification is attracting increasing interest because of its important role in law enforcement. Although the use of various fingerprint features might be required for successful latent fingerprint identification, methods based on minutiae are often readily applicable and commonly outperform other methods. However, as many fingerprint feature representations exist, we sought to determine if the selection of feature representation has an impact on the performance of automated fingerprint identification systems. In this paper, we review the most prominent fingerprint feature representations reported in the literature, identify trends in fingerprint feature representation, and observe that representations designed for verification are commonly used in latent fingerprint identification. We aim to evaluate the performance of the most popular fingerprint feature representations over a common latent fingerprint database. Therefore, we introduce and apply a protocol that evaluates minutia descriptors for latent fingerprint identification in terms of the identification rate plotted in the cumulative match characteristic (CMC) curve. From our experiments, we found that all the evaluated minutia descriptors obtained identification rates lower than 10% for Rank-1 and 24% for Rank-100 comparing the minutiae in the database NIST SD27, illustrating the need of new minutia descriptors for latent fingerprint identification.
51 citations
Cites methods from "Hierarchical fusion for matching si..."
...4%) using Fingercode [64] for latent-to-latent fingerprint matching on the IIIT-D latent database [66], the lowest among seven matching algorithms....
[...]
References
More filters
01 Jan 2006
TL;DR: In this paper, the authors explored the hypothesis that an examiner can, after a thorough analysis, successfully determine whether two or more latent impressions were deposited at the same time, and found that when making a definitive determination of either true or false, the participants were correct nearly 88% of the time.
Abstract: In December 2005, the Supreme Judicial Court of Massachusetts ruled that applying the ACE-V methodology to simultaneous impressions did not satisfy the requirements set forth in Daubert. Specifically, the Court stated that there was insufficient research on the topic of simultaneous impressions. This paper explores the hypothesis that an examiner can, after a thorough analysis, successfully determine whether two or more latent impressions were deposited at the same time. The study consisted of a series of thirty (30) latent impressions that were sent to volunteer latent print examiners around the world. Their task was to examine each impression and apply ACE-V to determine whether the impressions were truly simultaneous in nature. The data indicate that when making a definitive determination of either true or false, the participants were correct nearly 88% of the time.
6 citations
"Hierarchical fusion for matching si..." refers methods in this paper
...In 2006, Black [8] conducted the first experiments to study the application of ACE-V methodology for simultaneous impressions....
[...]
28 Sep 2009
TL;DR: This paper presents a semi-automatic approach to process the impressions of any individual using a fingerprint database that contains simultaneous latent impressions and analyzes the performance of the proposed approach obtained by matching simultaneous impressions with the gallery database.
Abstract: Recent cases such as Commonwealth v Patterson show that there is a lack of research in how to process and recognize simultaneous fingerprint impressions, especially when none of the latent prints in the cluster could be individually matched. SWGFAST released the first version of the standard on simultaneous impression examination that can help fingerprint examiners to systematically compare latent simultaneous impressions to a known ten-print card. However, when the individual is not known, the simultaneous fingerprint impressions have to be compared using a large database of reference ten-prints, making the process very challenging. This paper introduces the research problem of identifying simultaneous latent fingerprint impressions to the community and presents a semi-automatic approach to process the impressions of any individual. The approach generates a list of top matches and latent fingerprint examiners can then examine them for individualization. Using a fingerprint database that contains simultaneous latent impressions, we analyze the performance of the proposed approach obtained by matching simultaneous impressions with the gallery database.
6 citations
"Hierarchical fusion for matching si..." refers methods in this paper
...[14] proposed the first semiautomated technique for simultaneous latent fingerprint matching....
[...]