• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.10
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• pp.1783-1798
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• 2011

Recently, a cryptographic construct, called fuzzy vault, has been proposed for crypto-biometric systems, and some implementations for fingerprint have been reported to protect the stored fingerprint template by hiding the fingerprint features. In this paper, we implement the fuzzy fingerprint vault, combining fingerprint verification and fuzzy vault scheme to protect fingerprint templates. To implement the fuzzy fingerprint vault as a complete system, we have to consider several practical issues such as automatic fingerprint alignment, verification accuracy, execution time, error correcting code, etc. In addition, to protect the fuzzy fingerprint vault from the correlation attack, we propose an approach to insert chaffs in a structured way such that distinguishing the fingerprint minutiae and the chaff points obtained from two applications is computationally hard. Based on the experimental results, we confirm that the proposed approach provides higher security than inserting chaffs randomly without a significant degradation of the verification accuracy, and our implementation can be used for real applications.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.2
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• pp.73-80
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• 2006

Fingerprint-based verification system has been used for a very long time. Because of their well-known uniqueness and immutability, fingerprint is one of the most widely used biometric features. However, fingerprint identification system has such a critical weakness that the performance of verification is reduced drastically for a poor input fingerprint. In this paper, an image enhancement algorithm using enhanced direction and enhanced binary and aiming image is used to mitigate the problem in the preprocessing. The goal of image enhancement is to estimate the quality of input fingerprint image and to improve the clarity of ridge and valley structures of input fingerprint image. Also, a ridge orientation extraction method using index table is proposed to improve the speed of verification. It is shown by the experiments that proposed fingerprint verification system improves the minutiae extraction accuracy and performance of verification.

• Journal of the Korea Society of Computer and Information
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• v.10 no.4 s.36
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• pp.203-211
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• 2005

In this paper, we propose a new automatic fingerprint identification system that identifies individuals in large databases. The algorithm consists of three steps; preprocessing, classification, and matching, in the classification. we present a new classification technique based on the statistical approach for directional image distribution. In matching, we also describe improved minutiae candidate pair extraction algorithm that is faster and more accurate than existing algorithm. In matching stage, we extract fingerprint minutiaes from its thinned image for accuracy, and introduce matching process using minutiae linking information. Introduction of linking information into the minutiae matching process is a simple but accurate way, which solves the problem of reference minutiae pair selection in comparison stage of two fingerprints quickly. This algorithm is invariant to translation and rotation of fingerprint. The proposed system was tested on 1000 fingerprint images from the semiconductor chip style scanner. Experimental results reveal false acceptance rate is decreased and genuine acceptance rate is increased than existing method.

• The KIPS Transactions:PartB
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• v.12B no.2 s.98
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• pp.123-130
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• 2005

In this paper, fingerprint identification algorithm using pixel direction factor in blocks is proposed to minimize false acceptance ratio and to apply security system. The proposed algorithm is that a fingerprint image is divided by 16 blocks, then feature parameters which have direct factors of $0^{\circ},\;45^{\circ},\;90^{\circ}\;and\;135^{\circ}$ is extracted for each block. Membership function of a reference fingerprint and an input fingerprint for the extracted parameters is calculated, then identification of two fingerprint is distinguished using fuzzy inference. False acceptance ratio is evaluated about different fingerprints of In kinds regardless of sex and shape which are obtained from adults, and false rejection ratio is evaluated about fingerprints which are obtained by adding fingerprints of 10 kinds on different fingerprints of 100 kinds. The experiment results is that false acceptance ratio is average $0.34\%$ about experiment of 4,950 times, and false rejection ratio is average $3.7\%$ about experiment of 1,000 times. The proposed algerian is excellent for recognition rate and security.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.6
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• pp.1060-1069
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• 2016

In this paper, we introduce the fingerprint recognition system based on Radial Basis Function Neural Network(RBFNN). Fingerprints are classified as four types(Whole, Arch, Right roof, Left roof). The preprocessing methods such as fast fourier transform, normalization, calculation of ridge's direction, filtering with gabor filter, binarization and rotation algorithm, are used in order to extract the features on fingerprint images and then those features are considered as the inputs of the network. RBFNN uses Fuzzy C-Means(FCM) clustering in the hidden layer and polynomial functions such as linear, quadratic, and modified quadratic are defined as connection weights of the network. Particle Swarm Optimization (PSO) algorithm optimizes a number of essential parameters needed to improve the accuracy of RBFNN. Those optimized parameters include the number of clusters and the fuzzification coefficient used in the FCM algorithm, and the orders of polynomial of networks. The performance evaluation of the proposed fingerprint recognition system is illustrated with the use of fingerprint data sets that are collected through Anguli program.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.6
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• pp.88-100
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• 1998

In this paper, an algorithm for a real-time automatic fingerprint identification system is proposed. The fingerprint feature volume is extracted by considering distinct and local characteristics(such as intensity and image quality difference etc.) in fingerprint images, which makes the algorithm properly adaptive to various image acquisitionj methods. Also the matching technique is designed to be invariant on rotation, scaling and translation (RST) changes while being capable of real-time processing. And the classification of fingerprints is performed based on the ridge flow and the relations among singular points such as cores and deltas. The developed fingerprint identification algorithm has been applied to various sets of fingerprint images such as one from NIST(National Institute of Standards and Technology, USA), a pressed fingerprint database constructed according to Korean population distributions in sex, ages and jobs, and a set of rolled-than-scanned fingerprint images. The overall performance of the algorithm has been analyzed and evaluated to the false rejection ratio of 0.07% while holding the false acceptance ratio of 0%.

• Journal of KIISE:Software and Applications
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• v.31 no.7
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• pp.911-921
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• 2004

Accurate minutiae extraction from input fingerprint images is one of the critical modules in robust automatic fingerprint identification system. However, the performance of a minutiae extraction is heavily dependent on the quality of the input fingerprint images. If the preprocessing is performed according to the fingerprint image characteristics in the image enhancement step, the system performance will be more robust. In this paper, we propose a knowledge-based preprocessing method, which extracts S features (the mean and variance of gray values, block directional difference, orientation change level, and ridge-valley thickness ratio) from the fingerprint images and analyzes image quality with Ward's clustering algorithm, and enhances the images with respect to oily/neutral/dry characteristics. Experimental results using NIST DB 4 and Inha University DB show that clustering algorithm distinguishes the image Quality characteristics well. In addition, the performance of the proposed method is assessed using quality index and block directional difference. The results indicate that the proposed method improves both the quality index and block directional difference.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.7
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• pp.1204-1209
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• 2001

According to the rapid development of information and communication, various services are offered using information and communication infrastructure for example e-commerce, internet banking, stock dealings, etc. This time, the most important problem is personal identification. But now secret number that is used to personal identification mostly can be misappropriated. To solve this problem, this paper proposes smart card identification system using 1 vs. 1 fingerprint matching. Information protection and security of smart card excel and use is convenient. And fingerprint becomes the focus of public attention in biometric field. Implemented system in this paper is based on PC. This system stores minutia that is fingerprint information into smart card and compare it with personal minutia. Therefore this system is sure to be on personal identification. If this system is applied to various services, safety degree of services will be enhanced.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.517-520
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• 2001

According to the rapid development of information and communication, various services are offered using information and communication infrastructure for example e-commerce, internet banking stork dealings, etc. This time, the most important problem is personal identification. But now secret number that is used to personal identification mostly can be misappropriated. To solve this problem, this paper proposes smart card identification system using 1 vs. 1 fingerprint matching. Information protection and security of smart card excel and use is convenient. And fingerprint becomes the focus of public attention in biometric field. Implemented system in this paper is based on PC. This system stores minutia that is fingerprint information into smart card and compare it with personal minutia. Therefore this system is sure to be on personal identification. If this system is applied to various services, safety degree of services will be enhanced.

• The Journal of the Korea Contents Association
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• v.17 no.9
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• pp.132-144
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• 2017

The fingerprint classification of categorizing fingerprints by classes should be used in order to improve the processing speed and accuracy in a fingerprint recognition system using a large database. The fingerprint classification methods extract features from the fingerprint ridges of a fingerprint and classify the fingerprint using learning and reasoning techniques based on the classes defined according to the flow and shape of the fingerprint ridges. In earlier days, many researches have been conducted using NIST database acquired by pressing or rolling finger against a paper. However, as automated systems using live-scan scanners for fingerprint recognition have become popular, researches using fingerprint images obtained by live-scan scanners, such as fingerprint data provided by FVC, are increasing. And these days the methods of fingerprint classification using Deep Learning have proposed. In this paper, we investigate the trends of fingerprint classification technology and compare the classification performance of the technology. We desire to assist fingerprint classification research with increasing large fingerprint database in improving the performance by mentioning the necessity of fingerprint classification research with consideration for fingerprint images based on live-scan scanners and analyzing fingerprint classification using deep learning.