• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.18 no.3
• /
• pp.61-68
• /
• 2008

In this paper, we propose a new method to assess fingerprint image quality. In the proposed method, analysis of local variance of image's gray values, local orientation, minutiae density, size and position is applied. Especially by using position information of inputted fingerprint images, partial fingerprint images are filtered and recognition performance is improved. In the experimental results, quality threshold value for improving performance can be decided by analysis of correlation between image quality and recognition rate.

• The Korean Journal of Applied Statistics
• /
• v.25 no.6
• /
• pp.1027-1036
• /
• 2012

Among various biometrics recognition systems, statistical fingerprint recognition matching methods are considered using minutiae on fingerprints. We define similarity distance measures based on the coordinate and angle of the minutiae, and suggest a fingerprint recognition model following statistical distributions. We could obtain confidence intervals of similarity distance for the same and different persons, and optimal thresholds to minimize two kinds of error rates for distance distributions. It is found that the two confidence intervals of the same and different persons are not overlapped and that the optimal threshold locates between two confidence intervals. Hence an alternative statistical matching method can be suggested by using nonoverlapped confidence intervals and optimal thresholds obtained from the distributions of similarity distances.

• Proceedings of the IEEK Conference
• /
• 2005.11a
• /
• pp.355-358
• /
• 2005

Fingerprint recognition systems are the most widely used in biometrics for personal authentication. As they become more familiar, the security weaknesses of fingerprint sensors are becoming better known. In this paper, we propose a liveness detection method that applies correlation filter to the fingerprint recognition systems. The physiological characteristic of sweat pore, observed only in live people, is used as a measure to classify 'live' fingers from 'spoof' fingers. Previous works show that detection of sweat pores and perspiration patterns in fingerprint images can be used as an anti-spoofing measure. These methods don't consider the characteristic of pores in each individual. We construct the correlation filters of each individual which are composed of their pore information. We make the final decision about the "livens" of fingerprint using correlation output. The proposed algorithm was applied to a data set of 110 live, 110 spoof fingerprint images from optical fingerprint scanner and achieved classification rate of 80%.

• Journal of the Korea Computer Industry Society
• /
• v.3 no.12
• /
• pp.1775-1784
• /
• 2002

Fingerprint recognition technology is used in many biometrics field accordingly essential feature of fingerprint image and the study is progressing. However development is not perfect in performance of the fingerprint recognition and application of the usual life. In the paper, we study various necessity of preprocessing according to algorithm and circumstances of authentication system in automatic information machine. We prove that system circumstance and optation of fingerprints image effectively is the important factor by using optical fingerprint input device and scanning the fingerprint in ID card. And then we present correct and fast computation method for improving image and feature extraction of fingerprint. Also we study effective algorithm implementation of total system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2006.05a
• /
• pp.192-195
• /
• 2006

In this paper, we discuss the user-customized interaction for intelligent home environments. The interactive system is based upon the integrated techniques using speech recognition and fingerprint verification. For essential modules, the speech recognition and synthesis were basically used for a virtual interaction between the user and the proposed system. In experiments, particularly, the real-time speech recognizer based on the HM-Net(Hidden Markov Network) was incorporated into the integrated system. Besides, the fingerprint verification was adopted to customize home environments for a specific user. In evaluation, the results showed that the proposed system was easy to use for intelligent home environments, even though the performance of the speech recognizer was not better than the simulation results owing to the noisy environments

• Journal of the Korea Society for Simulation
• /
• v.19 no.1
• /
• pp.143-151
• /
• 2010

Fingerprint classification is a step to increase the efficiency of an 1:N fingerprint recognition system and plays a role to reduce the matching time of fingerprint and to increase accuracy of recognition. It is difficult to classify fingerprints, because the ridge pattern of each fingerprint class has an overlapping characteristic with more than one class, fingerprint images may include a lot of noise and an input condition is an exceptional case. In this paper, we propose a novel approach to design a stochastic model and to accomplish fingerprint classification using a directional characteristic of fingerprints for an effective classification of various qualities. We compute the directional value by searching a fingerprint ridge pixel by pixel and extract a directional characteristic by merging a computed directional value by fixed pixels unit. The modified Markov model of each fingerprint class is generated using Markov model which is a stochastic information extraction and a recognition method by extracted directional characteristic. The weight list of classification model of each class is decided by analyzing the state transition matrixes of the generated Markov model of each class and the optimized value which improves the performance of fingerprint classification using GA (Genetic Algorithm) is estimated. The performance of the optimized classification model by GA is superior to the model before the optimization by the experiment result of applying the fingerprint database of various qualities to the optimized model by GA. And the proposed method effectively achieved fingerprint classification to exceptional input conditions because this approach is independent of the existence and nonexistence of singular points by the result of analyzing the fingerprint database which is used to the experiments.

• Journal of Internet Computing and Services
• /
• v.21 no.2
• /
• pp.65-72
• /
• 2020

In this paper, a USB module with fingerprint recognition was designed as a distributed node of blockchain on distributed ID (DID, distributed ID) for user identification. This biometric-linked fingerprint recognition device was verified for the real-time authentication process of authentication transaction with FIDO(Fast IDentity Online) server. Blockchain DID-based services were proposed like as a method of individual TV rating survey, and recommending service for customized shopping channels, and crypto-currency, too. This DID based remote service can be improved by recognizing of channel-changing information through personal identification. The proposed information of production purchase can be shared by blockchain. And customized service can be provided for the utilization of purchase history in shoppingmall using distributed ID. As a result, this blockchain node-device and Samsung S10 Key-srore with FIDO service can be certified for additional transactions through various biometric authentication like fingerprint, and face recognition.

• The Journal of the Korea Contents Association
• /
• v.11 no.2
• /
• pp.79-87
• /
• 2011

Although products with the fingerprint recognition system currently show a rapid growth in quantity, it is also true that efforts to consider the product quality have been lacking until now. Accordingly, this paper analyzed technological elements with domestic and foreign market situations for products with the fingerprint recognition system to develop an evaluation model to support the quality increase by evaluating aspects of product quality for the knowledge information security, identifying the level of quality and deriving directions for improvements. A model for the reliability quality evaluation was constructed that can be applied comprehensively to non-functional elements that have not been done in the existing evaluations central to the security functions by analyzing requirements for the security, performance and reliability in consideration of features on products. It is considered that this paper can make contributions to the overall quality increase for products with the knowledge information security by reflecting features and trends for the fingerprint recognition products and building a model for the reliability and evaluation to perform evaluations by product.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.44 no.3
• /
• pp.61-69
• /
• 2007

This paper proposes new preprocessing algorithm to extract minutiae in the process of fingerprint recognition. Fingerprint images quality enhancement is a topic phase to ensure good performance in a topic phase to ensure good performance in a Automatic Fingerprint Identification System(AFIS) based on minutiae matching. This paper proposes an algorithm to improve fingerprint image preprocessing to extract minutiae accurately based on directional filter. We improved the suitability of low quality fingerprint images to better suit fingerprint recognition by using valid ridge vector and ridge probability of fingerprint images. With the proposed fingerprint improvement algorithm, noise is removed and presumed ridges are more clearly ascertained. The algorithm is based on five step: computation of effective ridge vector, computation of ridge probability, noise reduction, ridge emphasis, and orientation compensation and frequency estimation. The performance of the proposed approach has been evaluated on two set of images: the first one is self collected using a capacitive semiconductor sensor and second one is DB3 database from Fingerprint Verification Competition (FVC).

• Journal of the Institute of Convergence Signal Processing
• /
• v.6 no.2
• /
• pp.67-73
• /
• 2005

Recently, the social requirement of personal identification techniques has been increasing. Fingerprint recognition is one of the biometries methods that has been widely used for this requirement. This paper proposes the fingerprint matching algorithm that uses the information of the ridge shapes of minutiae. In which, the data of the ridge shape are expressed in one-dimensional discrete-time signals. In our algorithm, we obtain one-dimensional discrete-time signals for ridge at every minutiae from input and registered fingerprints, and find pairs of minutia which have the similar ridge shape by comparing input fingerprint with registered fingerprint, thereafter we find candidates of rotation angle and moving displacement from the pairs of similar minutia, and obtain the final rotation angle and moving displacement value from those candidates set by using clustering method. After that, we align an input fingerprint by using obtained data, and calculate the matching rate by counting the number of corresponded pairs of minutia within the overlapped area of an input and registered fingerprints. As a result of experiment, false rejection rate(FRR) of $18.0\%$ at false acceptance rate(FAR) of $0.79\%$ is achieved.