On separating overlapped fingerprints

Chen, Fanglin; Feng, Jianjiang; Zhou, Jie

doi:10.1109/btas.2010.5634483

Cited by 15 publications

(59 citation statements)

References 23 publications

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“…In our work, a backpropagation algorithm is used as a learning algorithm to train and test the network. In this system, we determined the TAR and ET values for the overlapped and non-overlapped images for various existing algorithms [4][5][6]. The achieved results were compared with the existing approaches as shown in Table 9, which proves that our proposed algorithm has achieved more accuracy.…”

Section: Resultsmentioning

confidence: 76%

“…Singh et al [16] develop Independent Component Analysis (ICA) to independent, covered fingerprints images, without any partition calculation for overlapped fingerprint images. Fanglin et al [4] proposed separation of overlapped fingerprints taking help from the fingerprint experts. The orientation fields are marked manually in the overlapped images.…”

Section: Prior Work and Problem Formulationmentioning

confidence: 99%

“…Most of the existing fingerprint-matching algorithms [1,[3][4][5][8][9][10][11][12][13], and [14] failed to match the overlapped images in an efficient manner. VeriFinger and FingerTec algorithms are unable to split the two fingerprints effectively, and there is no successful extraction of the ridges in the overlapped area.…”

Section: Prior Work and Problem Formulationmentioning

confidence: 99%

“…In addition, an overlapped image can be split for identification using the existing algorithms [4][5][6] and [17]. An overlapped fingerprint image is partitioned into nonoverlapping blocks with 32 9 32 pixels.…”

Section: Overlapped Fingerprint Separationmentioning

confidence: 99%

“…Particularly during criminal investigations, there is a chance that the fingerprint experts misjudge in identifying a person [3]. Determining the distinct features of prints overlapped with either a finger or the background can be dangerous and time consuming [4][5][6]. Due to overlapping fingerprints, recognition may not be possible even if the fingerprint templates for the images are available.…”

Section: Introductionmentioning

confidence: 98%

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An Efficient Automatic Overlapped Fingerprint Identification and Recognition Using ANFIS Classifier

Jeyanthi

Maheswari

Venkatesh

2015

Int. J. Fuzzy Syst.

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The Automatic Fingerprint Recognition System plays an important role in forensics and law enforcement applications. The objective of the proposed system in the current study is to identify and separate overlapped fingerprint images automatically using an Adaptive Neuro Fuzzy Inference System (ANFIS) Classifier. There are various issues that have been identified, which need to be addressed to develop the scope of light-out fingerprint recognition system. The latent fingerprint images can be overlapped in crime scenes. During investigations, there are several possibilities for acquiring damaged or overlapped fingerprint images. The proposed system analyzes and identifies the overlapped images using an ANFIS Classifier. This paper also proposes a novel algorithm for the separation of overlapped images. The proposed work is designed to retrieve fast and accurate data using fingerprint identification for the overlapped images. Extensive experiments are performed on the FVC 2006 DB1-A, DB2-A, NIST SD27 and SLF databases. The experimental results are highly promising and outperform the previous systems in identifying the overlapped images. Our proposed system separates those overlapped fingerprints more accurately and robustly. The achieved results confirmed that the proposed automatic fingerprint recognition system has higher possibility of overlapped fingerprint detection.

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Section: Resultsmentioning

confidence: 76%

Section: Prior Work and Problem Formulationmentioning

confidence: 99%

Section: Prior Work and Problem Formulationmentioning

confidence: 99%

Section: Overlapped Fingerprint Separationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

See 3 more Smart Citations

An Efficient Automatic Overlapped Fingerprint Identification and Recognition Using ANFIS Classifier

Jeyanthi

Maheswari

Venkatesh

2015

Int. J. Fuzzy Syst.

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Privacy Preserving Challenges: New Design Aspects for Latent Fingerprint Detection Systems with Contact-Less Sensors for Future Preventive Applications in Airport Luggage Handling

Hildebrandt

Dittmann

Pocs

et al. 2011

Lecture Notes in Computer Science

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Context‐based approach of separating contactless captured high‐resolution overlapped latent fingerprints

et al. 2014

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Overlapped latent fingerprints occurring at crime scenes challenge forensic investigations, as they cannot be properly processed unless separated. Addressing this, Chen et al. proposed a relaxation-labelling-based approach on simulated samples, improved by Feng et al. for conventionally developed latent ones. As the development of advanced contactless nanometrerange sensing technology keeps broadening the vision of forensics, the authors use a chromatic white light sensor for contactless non-invasive acquisition. This preserves the fingerprints for further investigations and enhances existing separation techniques. Motivated by the trend in dactyloscopy that investigations now not only aim at identifications but also retrieving further context of the fingerprints (e.g. chemical composition, age), a context-based separation approach is suggested for highresolution samples of overlapped latent fingerprints. The author's conception of context-aware data processing is introduced to analyse the context in this forensic scenario, yielding an enhanced separation algorithm with optimised parameters. Two test sets are generated for evaluation, one consisting of 60 authentic overlapped fingerprints on three substrates and the other of 100 conventionally developed latent samples from the work of Feng et al. An equal error rate of 5.7% is achieved on the first test set, which shows improvement over their previous work, and 17.9% on the second.

show abstract

On separating overlapped fingerprints

Cited by 15 publications

References 23 publications

An Efficient Automatic Overlapped Fingerprint Identification and Recognition Using ANFIS Classifier

An Efficient Automatic Overlapped Fingerprint Identification and Recognition Using ANFIS Classifier

Privacy Preserving Challenges: New Design Aspects for Latent Fingerprint Detection Systems with Contact-Less Sensors for Future Preventive Applications in Airport Luggage Handling

Context‐based approach of separating contactless captured high‐resolution overlapped latent fingerprints

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