• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.8
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• pp.530-536
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• 2020

The use of minutiae by fingerprint readers is robust against presentation attacks, but one weakness is that the mismatch rate is high. Therefore, minutiae tend to be used with skeleton images. There have been many studies on security vulnerabilities in the characteristics of minutiae, but vulnerability studies on the skeleton are weak, so this study attempts to analyze the vulnerability of presentation attacks against the skeleton. To this end, we propose a method based on the skeleton to recover the original fingerprint using a learning algorithm. The proposed method includes a new learning model, Pix2Pix, which adds a latent vector to the existing Pix2Pix model, thereby generating a natural fingerprint. In the experimental results, the original fingerprint is restored using the proposed machine learning, and then, the restored fingerprint is the input for the fingerprint reader in order to achieve a good recognition rate. Thus, this study verifies that fingerprint readers using the skeleton are vulnerable to presentation attacks. The approach presented in this paper is expected to be useful in a variety of applications concerning fingerprint restoration, video security, and biometrics.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.1
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• pp.55-63
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• 2008

Ridge orientations of fingerprint image are crucial informations in many parts of fingerprint recognition such as enhancement, matching and classification. Therefore it is essential to extract the ridge orientations of image accurately because it directly affects the performance of the system. The two main properties of ridge orientation are 1) global characteristic(gradual change in whole part of fingerprint) and 2) local characteristic(abrupt change around core and delta points). When we only consider the local characteristic, estimated ridge orientations are well around singular points but not robust to noise. When the global characteristic is only considered, to estimate ridge orientation is robust to noise but cannot represent the orientation around singular points. In this paper, we propose a novel method for estimating ridge orientation which represents local characteristic specifically as well as be robust to noise. We reduce the noise caused by scar using iterative outlier rejection. We apply adaptive measurement resolution in each fingerprint area to estimate the ridge orientation around singular points accurately. We evaluate the performance of proposed method using synthetic fingerprint and FVC 2002 DB. We compare the accuracy of ridge orientation. The performance of fingerprint authentication system is evaluated using FVC 2002 DB.

• Journal of Korea Multimedia Society
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• v.9 no.10
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• pp.1304-1313
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• 2006

Biometric-based authentication can provide strong security guarantee about the identity of users. However, security of biometric data is particularly important as the compromise of the data will be permanent. In this paper, we propose a secure and efficient protocol to transmit fingerprint images from a fingerprint sensor to a client by exploiting characteristics of fingerprint images. Because the fingerprint sensor is computationally limited, however, such encryption algorithm may not be applied to the full fingerprint images in real-time. To reduce the computational workload on the resource-constrained sensor, we apply the encryption algorithm to a specific bitplane of each pixel of the fingerprint image. We use the LSB as specific bitplane instead of MSB used to encrypt general multimedia contents because simple attacks can reveal the fingerprint ridge information even from the MSB-based encryption. Based on the experimental results, our proposed algorithm can reduce the execution time of the full encryption by a factor of six and guarantee both the integrity and the confidentiality without any leakage of the ridge information.

• The KIPS Transactions:PartB
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• v.10B no.5
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• pp.497-502
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• 2003

Fingerprint classification plays a role of reduction of precise joining time and improvement of the accuracy in a large volume of database. Patterns of fingerprint are classified as 5 patterns : left loop, right loop, arch, whorl, and tented arch by numbers and the location of core point and delta point. The existing fingerprint classification is useful in a captured fingerprint image of core point and delta point using paper and ink. However, this system is unapplicable in modern Automatic Fingerprint Identification System (AFIS) because of problems such as size of input and way of input. To solve the problem, this study is to suggest the way of being able to improve accuracy of fingerprint by fingerprint classification based on the entropy of ridges using fingerprint captured mage of core point and prove this through the experiment.

• The KIPS Transactions:PartB
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• v.9B no.5
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• pp.653-662
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• 2002

Fingerprint recognition is a task to find a matching pattern in a database for a specific persons fingerprint. To accomplish this task, preprocessing, classification, and matching steps are taken for a large-scale fingerprint database but only the matching step is taken without classification for a small-scale database. The primary matching method is based on minutiae (ridge ending point, bifurcation). This matching method, however, requires a very complex computation to extract minutiae and match minutiae-to-minutiae accurately due to translation, rotation, nonlinear deformation of fingerprint and occurrence of spurious minutiae. In addition, this method requires a laborious preprocessing step in order to improve the quality of fingerprint Images. This paper proposes a new simple method to eliminate these problems. With this method, Gabor variance is used instead of minutiae for fingerprint recognition. The Gabor variance is computed from Gabor features that result from filtering a fingerprint image through Gabor filter. In this paper, this method is described and its test result is shown, demonstrating the potential of using this new method for fingerprint recognition.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.3
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• pp.11-25
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• 2009

Fingerprint sample quality is one of major factors influencing the matching performance of fingerprint recognition systems. The error rates of fingerprint recognition systems can be decreased significantly by removing poor quality fingerprints. The purpose of this paper is to assess the effectiveness of individual sample quality measures on the performance of minutiae-based fingerprint recognition algorithms. Initially, the authors examined the various factors that influenced the matching performance of the minutiae-based fingerprint recognition algorithms. Then, the existing measures for fingerprint sample quality were studied and the more effective quality measures were selected and compared with two image quality software packages, (NFIQ from NIST, and QualityCheck from Aware Inc.) in terms of matching performance of a commercial fingerprint matcher (Verifinger 5.0 from Neurotechnologija). The experimental results over various Fingerprint Verification Competition (FVC) datasets show that even a single sample quality measure can enhance the matching performance effectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.8
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• pp.1897-1904
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• 1996

This study intends to extract the efficient spectrum characteristics of the fingerpriint image in the fourier domain and to apply them for image enhancement. In order to effectively acquire the spectrum characteristics of the fingerprint in the fourier domain, I set up a 1*64 window as a processing unit and, combining various kinds of the record and overlap lengths, made the power spectrum density estimate for each of those combinations. each spectrum characeristic acquired was applied to a re-synthesis process of the fingerprint image, and, through comparisons and evaluations of the resultant images, an improved gray scale image could be obtained. The validity of this algorithm could be confirmed by the comparison and evaluation fo the binary images which were grained on the established method and the one I used in this experiment.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.3
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• pp.227-230
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• 2002

An important preprocessing for fingerprint recognition is the binarization operation, which takes as an input gray-scale image and returns a binary image as the output. The difficult in performing binarization is to find an appropriate threshold value. This paper presents a new adaptive binarization method, which determines the threshold value according to the brightness of local ridges and valleys. We experimentally show that the presented method results in better performance than a traditional method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.14 no.6
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• pp.611-620
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• 1989

In this paper, Fingerprint matching method which is able to confirm one's identity using microcomputer is discussed. In matching method, fingerprint image is thinned and we extracted feature point data which is composed of position and direction of end-point and branch-point. Identification is conducted by decision of disagreement between reference finger print and input fingerprint us ing this extracted data. After averaging and binariztion process, thining method is conducted. Restoration process is carried out to seek precise feature pointdatd. We compensate position difference of reference fingerprint and input fingerprint, which is divied end-point and branch-point, and translated and rotated its position. Using this compensdate difference of position, we decide whether fingerp-print identity is true or not.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.8
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• pp.1655-1666
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• 2015

In this paper, user-position estimation method is proposed by using a single camera for both indoor and outdoor environments. Conventionally, the GPS of RF-based estimation methods have been widely studied in the literature for outdoor and indoor environments, respectively. Each method is useful only for indoor or outdoor environment. In this context, this study adopts a vision-based approach which can be commonly applicable to both environments. Since the distance or position cannot be extracted from a single still image, the reference images pro-stored in image database are used to identify the current position from the single still image captured by a single camera. The reference image is tagged with its captured position. To find the reference image which is the most similar to the current image, the SURF algorithm is used for feature extraction. The outliers in extracted features are discarded by using RANSAC algorithm. The performance of the proposed method is evaluated for two buildings and their outsides for both indoor and outdoor environments, respectively.