Neural Network based Minutiae Extraction from Skeletonized Fingerprints

Bartunek, Josef Ström; Nilsson, Mikael; Nordberg, Jörgen; Claesson, Ingvar

doi:10.1109/tencon.2006.344104

Cited by 10 publications

(9 citation statements)

References 12 publications

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“…The minutiae based efficient data structure technique called kd-tree is discussed in [8]. A neural network can be used for detecting the various minutiae points of a fingerprint [9]. The above minutiae based matching algorithms do not give a satisfactory matching rate because ridge ending and bifurcation do not give enough information for matching.…”

Section: Related Workmentioning

confidence: 99%

Hartley Transform Based Fingerprint Matching

Bharkad¹,

Kokare²

2012

Journal of Information Processing Systems

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Abstract-TheHartley transform based feature extraction method is proposed for fingerprint matching. Hartley transform is applied on a smaller region that has been cropped around the core point. The performance of this proposed method is evaluated based on the standard database of Bologna University and the database of the FVC2002. We used the city block distance to compute the similarity between the test fingerprint and database fingerprint image. The results obtained are compared with the discrete wavelet transform (DWT) based method. The experimental results show that, the proposed method reduces the false acceptance rate (FAR) from 21.48% to 16.74 % based on the database of Bologna University and from 31.29% to 28.69% based on the FVC2002 database.

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Section: Related Workmentioning

confidence: 99%

Hartley Transform Based Fingerprint Matching

Bharkad¹,

Kokare²

2012

Journal of Information Processing Systems

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“…Neural networks [7,8], fuzzy logic [9], Gabor filters [10], line tracing algorithms [11,13], orientation based methods [14] and simple convolutional filters [15] are some of the common methods to extract the minutiae points. However, line tracing algorithms and convolutional filters are time consuming.…”

Section: Introductionmentioning

confidence: 99%

Novel Feature Extraction Methodology with Evaluation in Artificial Neural Networks Based Fingerprint Recognition System

Kahraman

Taşkıran

2018

Teh. vjesn.

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Fingerprint recognition is one of the most common biometric recognition systems that includes feature extraction and decision modules. In this work, these modules are achieved via artificial neural networks and image processing operations. The aim of the work is to define a new method that requires less computational load and storage capacity, can be an alternative to existing methods, has high fault tolerance, convenient for fraud measures, and is suitable for development. In order to extract the feature points called minutia points of each fingerprint sample, Multilayer Perceptron algorithm is used. Furthermore, the center of the fingerprint is also determined using an improved orientation map. The proposed method gives approximate position information of minutiae points with respect to the core point using a fairly simple, orientation map-based method that provides ease of operation, but with the use of artificial neurons with high fault tolerance, this method has been turned to an advantage. After feature extraction, General Regression Neural Network is used for identification. The system algorithm is evaluated in UPEK and FVC2000 database. The accuracies without rejection of bad images for the database are 95.57% and 91.38% for UPEK and FVC2000 respectively.

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“…Neural networks have been used in problems of fingerprint recognition in several ways. In [2] and [3] the parameters extraction is performed using neural networks and in [4], a comparison between several neural networks for fingerprint classification is performed. Despite that, the neural networks use for fingerprint matching is not well explored.…”

Section: Introductionmentioning

confidence: 99%

A Fingerprint Matching Algorithm Based On Minutiae And Local Ridge Orientation

Salmento¹,

Xavier²,

Peralva³

et al. 2016

Anais Do 10. Congresso Brasileiro De Inteligência Computacional

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Resumo -Este artigo apresenta um novo método de reconhecimento de impressões digitais baseado nas informações das minúcias extraídas e do campo de orientação da imagem, em que uma rede neural artificialé usada para realizar o casamento. O método proposto foi implementado em software e seu desempenho foi avaliado. O método proposto apresentou um bom desempenho para o banco de dados composto por imagens selecionadas do banco de impressões digitais de referência FVC2000.Palavras-chave -Biometria, Impressão Digital, Extração de Minúcias, Redes Neurais.Abstract -This paper presents a new method for fingerprint recognition based on information extracted from the minutiae and the orientation field from the image that uses an artificial neural network as a matching algorithm. The proposed method was implemented by software and its performance was evaluated.The proposed method presented a good performance for the data set used in this work which is composed by selected images from the FVC2000 database.

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Neural Network based Minutiae Extraction from Skeletonized Fingerprints

Cited by 10 publications

References 12 publications

Hartley Transform Based Fingerprint Matching

Hartley Transform Based Fingerprint Matching

Novel Feature Extraction Methodology with Evaluation in Artificial Neural Networks Based Fingerprint Recognition System

A Fingerprint Matching Algorithm Based On Minutiae And Local Ridge Orientation

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