• 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.

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.163-177
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• 2024

The fingerprint image quality relies on the clearness of separated ridges by valleys and the uniformity of the separation. The condition of skin still dominate the overall quality of the fingerprint. However, the identification performance of such system is very sensitive to the quality of the captured fingerprint image. Fingerprint image quality analysis and enhancement are useful in improving the performance of fingerprint identification systems. A fuzzy technique is introduced in this paper for both fingerprint image quality analysis and enhancement. First, the quality analysis is performed by extracting four features from a fingerprint image which are the local clarity score (LCS), global clarity score (GCS), ridge_valley thickness ratio (RVTR), and the Global Contrast Factor (GCF). A fuzzy logic technique that uses Mamdani fuzzy rule model is designed. The fuzzy inference system is able to analyse and determinate the fingerprint image type (oily, dry or neutral) based on the extracted feature values and the fuzzy inference rules. The percentages of the test fuzzy inference system for each type is as follow: For dry fingerprint the percentage is 81.33, for oily the percentage is 54.75, and for neutral the percentage is 68.48. Secondly, a fuzzy morphology is applied to enhance the dry and oily fingerprint images. The fuzzy morphology method improves the quality of a fingerprint image, thus improving the performance of the fingerprint identification system significantly. All experimental work which was done for both quality analysis and image enhancement was done using the DB_ITS_2009 database which is a private database collected by the department of electrical engineering, institute of technology Sepuluh Nopember Surabaya, Indonesia. The performance evaluation was done using the Feature Similarity index (FSIM). Where the FSIM is an image quality assessment (IQA) metric, which uses computational models to measure the image quality consistently with subjective evaluations. The new proposed system outperformed the classical system by 900% for the dry fingerprint images and 14% for the oily fingerprint images.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.9
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• pp.887-893
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• 2012

In this paper, we propose a new approach to extract directional features based on directional patterns of each region in fingerprint images. The proposed approach computes the center of gravity to extract features from fingerprint images of various shapes. According to it, we divide a fingerprint image into four regions and compute the directional values of each region. To extract directional features of each region from a fingerprint image, we spilt direction values of ridges in a region into 18 classes and compute frequency distribution of each region. Through the result of our experiment using FVC2002 DB database acquired by electronic devices, we show that directional features are effectively extracted from various fingerprint images of exceptional inputs which lost all or part of singularities. To verify the performance of the proposed approach, we explained the process to model Arch, Left, Right and Whorl class using the extracted directional features of four regions and analyzed the classification result.

• 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 the Korea Institute of Information Security & Cryptology
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• v.16 no.4
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• pp.91-103
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• 2006

This paper proposes a methodology to evaluate the quality and level of difficulty of fingerprint image databases, which leads to objective evaluation for the performance of fingerprint recognition system. Influencing factors to fingerprint matching are defined and the matching performance between two fingerprint images is evaluated using segmentation and orientation filed. In this study, a hierarchical processing method is proposed to measure an orientation field, which is able to improve the matching speed and accuracy. The results of experiments demonstrate that the defined influencing factors can describe the characteristics of fingerprint databases. Level of difficulty for fingerprint databases enables the performance of fingerprint recognition algorithms to be evaluated and compared even with different databases.

• Journal of Internet of Things and Convergence
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• v.2 no.4
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• pp.35-39
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• 2016

This paper is about IoT(Internet of Things)-based indoor localization scheme. GPS and WiFi are widely used to estimate the location of things. However, GPS has drawback of poor reception and radio disturbance in doors. To estimate the location in WiFi-based method, the user collects the information by scanning nearby WiFi(s) and transferring the information to WiFi database server. This is a fingerprint method with disadvantage of having an additional DB server. IoT is the internetworking of things, and this is on rapid rise. I propose the IoT-based indoor localization scheme. Under the proposed method, a device internetworking with another device with its own location information like GPS coordinate can estimate its own location through RSSI. With more devices localizing its own, the localization accuracy goes high. The proposed method allows the user to estimate the location without GPS and WiFi DB server.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.20 no.3
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• pp.23-30
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• 2010

Compression techniques can be applied to large-scale fingerprint systems to store or transmit fingerprint data efficiently. In this paper, we investigate the effects of FBI WSQ fingerprint image compression on the performance of a fingerprint verification system using multiple linear regressions. We propose a maximum compression using fingerprint image quality score. Based on the experiments, we can confirm that the proposed approach can compress the fingerprint images up to 3 times more than the fixed compression ratio without significant degradation of the verification accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.6
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• pp.1327-1342
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• 2010

With the wide deployment of biometric authentication systems, several issues pertaining security and privacy of the biometric template have gained great attention from the research community. To resolve these issues, a number of biometric template protection methods have been proposed. However, the design of a template protection method to satisfy four criteria, namely diversity, revocability and non-invertibility is still a challenging task, especially performance degradation when template protection method is employed. In this paper, we propose a novel method to generate a revocable minutiae-based fingerprint template. The proposed method consists of feature extraction from fingerprint minutiae pairs, quantization, histogram binning, binarization and eventually binary bit-string generation. The contributions of our method are two fold: alignment-free and good performance. Various experiments on FVC2004 DB1 demonstrated the effectiveness of the proposed methods.

• Journal of KIISE
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• v.42 no.4
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• pp.419-426
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• 2015

This paper proposes a fingerprint verification system on a fuzzy vault with steganography for a smartphone. While biometric-based authentication can provide strong security, the biometric data must be handled carefully as it cannot be re-enrolled when it is revealed to other people. When the transformed data is used for authentication, the original biometric data can be protected. In this paper, we combine a fingerprint verification system with a fuzzy vault scheme to protect the fingerprint data of a smartphone user. In addition, the transformed data using a fuzzy vault scheme increases the security as it is concealed by the steganography scheme. The result of the experiment using fingerprint databases shows that the proposed scheme provides a high level of convenience and security for authentication of a smartphone having with a fingerprint sensor.

• The Journal of the Acoustical Society of Korea
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• v.32 no.5
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• pp.415-422
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• 2013

This paper proposes a robust binary audio fingerprinting method by minimizing hinge-loss function. In the proposed method, the type of fingerprints is binary, which is conducive in reducing the size of fingerprint DB. In general, the binarization of features for fingerprinting deteriorates the performance of fingerprinting system, such as robustness and discriminability. Thus it is necessary to minimize such performance loss. Since the similarity between two audio clips is represented by a hinge-like function, we propose a method to derive a binary fingerprinting by minimizing a hinge-loss function. The derived hinge-loss function is minimized by using the minimal loss hashing. Experiments over thousands of songs demonstrate that the identification performance of binary fingerprinting can be improved by minimizing the proposed hinge loss function.