• Korean Management Science Review
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• v.29 no.2
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• pp.79-90
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• 2012

Focusing on the rapid market penetration of smart phones, the importance of LBS (Location Based Service) is drastically increased. However, traditional GPS method has critical weakness caused by limited availability, such as indoor environment. WPS is newly attractive method as a widely applicable positioning method. In WPS, RSSI (Received Signal Strength Indication) data of all Wi-Fi APs (Access Point) are measured and stored into a huge database. The stored RSSI data in database make single radio fingerprint map. By the radio fingerprint map, we can estimate the actual position of target point. The essential factor of radio fingerprint database is data integrity of RSSI. Because of millions of APs in urban area, RSSI measurement data are seriously contaminated. Therefore, we present the unified filtering method for RSSI measurement data. As the results of filtering, we can show the effectiveness of suggested method in practical positioning system of mobile operator.

• The Transactions of the Korea Information Processing Society
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• v.6 no.10
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• pp.2816-2822
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• 1999

In this paper, a fast thinning method for fingerprint image by separating end and bifurcation region is proposed. To detect feature points in automatic fingerprint identification system, thinning of fingerprint is essential. The end and bifurcation regions in ridge line are separated by means of run-length coding, and parallel thinning method is applied to the separated regions. The rest parts except the end and bifurcation regions are processed by connecting center points of each run. The performance of the proposed method has been evaluated by CPU processing time and thinness measurement. By the experimental results, the proposed method is fast and has high thinness value.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.5
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• pp.1113-1118
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• 2018

Fingerprint authentication is the most popular biometric in smart devices. However it has vulnerability to fake fingerprints. This paper shows that it is possible to pass fingerprint authentication of smartphone by creating counterfeit fingerprint without approval of legitimate users. As a technical countermeasure to prevent such a smudge-based attack, there has been proposed an under-screen Touch ID with a slide bar, which is a method of removing the fingerprint trail by dragging the UI to the side after fingerprint authentication on the touch screen. In this paper, we analyze how the proposed attack method and mitigation are perceived by actual user through 61 user survey.

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

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.2
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• pp.536-544
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• 2017

Wireless RSSI (Received Signal Strength Indication) fingerprinting is one of the most popular methods for indoor positioning as it provides reasonable accuracy while being able to exploit existing wireless infrastructure. However, the process of radio map construction (aka fingerprint calibration) is laborious and time consuming as precise physical coordinates and wireless signals have to be measured at multiple locations of target environment. This paper proposes a method to build the map from a combination of RSSIs without location information collected in a crowdsourcing fashion, and a handful of labeled RSSIs using a semi-supervised self organizing map learning algorithm. Experiment on simulated data shows promising results as the method is able to recover the full map effectively with only 1% RSSI samples from the fingerprint database.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.446-449
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• 2000

A direct RTI(Rotation and translation invariant) fingerprint identification is proposed using the GCMs(generalized complex moments) and Gabor filter-based features from the grey level fingerprint around core point. The core point is located as reference point for the translation invariant matching. And its symmetry axis is detected for the rotation invariant matching from its neighboring region centered at the core point. And then, fingerprint is divided into non-overlapping blocks with respect to the core point and, in contrast to minutiae-based method using various processing steps, features are directly extracted from the blocked grey level fingerprint using Gabor filter, which provides information contained in a particular orientation in the image. The Proposed fingerprint identification is based on the Euclidean distance of the corresponding Gabor features between the input and the template fingerprint. Experiments are conducted on 300 ${\times}$ 300 fingerprints obtained from the CMOS sensor with 500 dpi resolution, and the proposed method could obtain 97% identification rate.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.4
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• pp.854-860
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• 2004

The result of fingerprint matching is different as the quality or the state of input fingerprint image. We can extract the false direction information when the quality of fingerprint is degraded by the noise or the scars of the ridges. The information of the direction is very important for the elimination of the false minutia, the measurement of the ridge distance, matching, finding of cores and deltas. We need the method which can compensate or correct the false information of directions because the false directions include serious errors in the fingerprint recognition. We propose a method which can compensate or correct the false direction of fingerprint with a \alpha$-trimmed mean filter followed by LPF to reconstruct the false direction information when fingerprints are corrupted by scars.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.29-36
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• 2022

In deep learning classification tasks, most models frequently assume that all labels are available for the training datasets. As such strategies to learn new concepts from unlabeled datasets are scarce. In fingerprint classification tasks, most of the fingerprint datasets are labelled using the subject/individual and fingerprint datasets labelled with finger type classes are scarce. In this paper, authors have developed approaches of classifying fingerprint images using the majorly known fingerprint classes. Our study provides a flexible method to learn new classes of fingerprints. Our classifier model combines both the clustering technique and use of deep learning to cluster and hence label the fingerprint images into appropriate classes. The K means clustering strategy explores the label uncertainty and high-density regions from unlabeled data to be clustered. Using similarity index, five clusters are created. Deep learning is then used to train a model using a publicly known fingerprint dataset with known finger class types. A prediction technique is then employed to predict the classes of the clusters from the trained model. Our proposed model is better and has less computational costs in learning new classes and hence significantly saving on labelling costs of fingerprint images.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.65-68
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• 2002

In an automatic fingerprint recognition system, a thinning process after binarization is commonly used. However it gives rise to spurs and holes often causing many spurious minutiae. Thus, more elaborate postprocessing is urgently needed to remove such spurious minutiae. To overcome this problem, we present a method of extracting minutiae based on horizontal and vertical run-length encoding from a binary fingerprint image without thinning process. Experimental results show that the proposed method for extracting minutiae is fairly reliable and fast, when il is compared to other method adopting a thinning process.

• Phonetics and Speech Sciences
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• v.4 no.1
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• pp.77-87
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• 2012

Interest in music recognition has been growing dramatically after NHN and Daum released their mobile applications for music recognition in 2010. Methods in music recognition based on audio analysis fall into two categories: music recognition using audio fingerprint and Query-by-Singing/Humming (QBSH). While music recognition using audio fingerprint receives music as its input, QBSH involves taking a user-hummed melody. In this paper, research trends are described for music recognition using audio fingerprint, focusing on two methods: one based on fingerprint generation using energy difference between consecutive bands and the other based on hash key generation between peak points. Details presented in the representative papers of each method are introduced.