• Proceedings of the IEEK Conference
• /
• 2000.09a
• /
• pp.901-904
• /
• 2000

A direct authentication from gray-scale image, instead of the conventional multi-step preprocessing, is proposed using Gabor filter-based features from the gray-scale fingerprint around core point. The core point is located as a reference point for the translation invariant matching. And its principal 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 features are directly extracted form the blocked gray level fingerprint using Gabor filter. The proposed fingerprint authentication is based on the Euclidean distance between the corresponding Gabor features of the input and the template fingerprints. Experiments are conducted on 300${\times}$300 fingerprints obtained from a CMOS sensor with 500 dpi resolution, and the proposed method could lower the False Reject Rate(FRR) to 18.2% under False Acceptance Rate(FAR) of 0%.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37 no.8C
• /
• pp.731-740
• /
• 2012

To offer indoor location-aware services, the needs for efficient and accurate indoor localization system has been increased. In order to meet these requirement, we presented the BLIDx(Bidirectional Location ID exchange) protocol that is efficient localization system based on sensor network. The BLIDx protocol can cope with numerous mobile nodes simultaneously but the precision of the localization is too coarse because that uses cell based localization method. In this paper, in order to compensate for these disadvantage, we propose the fingerprint overlapping method by modifying a fingerprinting methods in WLAN, and localization system using proposed method was designed and implemented. Our experiments show that the proposed method is more accurate and robust to noise than fingerprinting method in WLAN. In this way, it was improved that low location precision of BLIDx protocol.

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

• Korean Journal of Optics and Photonics
• /
• v.31 no.3
• /
• pp.125-133
• /
• 2020

An innovative method for separating overlapping latent fingerprints, using laser-induced plasma spectroscopy (LIPS) combined with multivariate analysis, is reported in the current study. LIPS provides the capabilities of real-time analysis and high-speed scanning, as well as data regarding the chemical components of overlapping fingerprints. These spectra provide valuable chemical information for the forensic classification and reconstruction of overlapping latent fingerprints, by applying appropriate multivariate analysis. This study utilizes principal-component analysis (PCA) and partial-least-squares (PLS) techniques for the basis classification of four types of fingerprints from the LIPS spectra. The proposed method is successfully demonstrated through a classification example of four distinct latent fingerprints, using discrimination such as soft independent modeling of class analogy (SIMCA) and partial-least-squares discriminant analysis (PLS-DA). This demonstration develops an accuracy of more than 85% and is proven to be sufficiently robust. In addition, by laser-scanning analysis at a spatial interval of 125 ㎛, the overlapping fingerprints were separated as two-dimensional forms.

• Analytical Science and Technology
• /
• v.33 no.2
• /
• pp.86-97
• /
• 2020

Reconstruction and separation of explosive-contaminated overlapping fingerprints constitutes an analytical challenge of high significance in forensic sciences. Laser-induced breakdown spectroscopy (LIBS) allows real-time chemical mapping by detecting the light emissions from laser-induced plasma and can offer powerful means of fingerprint classification based on the chemical components of the sample. During recent years LIBS has been studied one of the spectroscopic techniques with larger capability for forensic sciences. However, despite of the great sensitivity, LIBS suffers from a limited detection due to difficulties in reconstruction of overlapping fingerprints. Here, the authors propose a simple, yet effective, method of using chemical mapping to separate and reconstruct the explosive-contaminated, overlapping fingerprints. A Q-switched Nd:YAG laser system (1064 nm), which allows the laser beam diameter and the area of the ablated crater to be controlled, was used to analyze the chemical compositions of eight samples of explosive-contaminated fingerprints (featuring two sample explosive and four individuals) via the LIBS. Then, the chemical validations were further performed by applying the Raman spectroscopy. The results were subjected to principal component and partial least-squares multivariate analyses, and showed the classification of contaminated fingerprints at higher than 91% accuracy. Robustness and sensitivity tests indicate that the novel method used here is effective for separating and reconstructing the overlapping fingerprints with explosive trace.

• Proceedings of the Korean Information Science Society Conference
• /
• 2011.06d
• /
• pp.308-310
• /
• 2011

최근 서비스 패러다임이 언제나 같은 서비스를 제공하는 수동적 형태의 서비스에서 현재의 상황에 맞게 (context-aware) 서비스를 제공하는 능동적 형태의 서비스로 변화하고 있다. 이때 현재 상황(context) 중에서 가장 중요한 정보가 위치정보이다. 따라서 효율적이면서도 정밀한 실내 위치인식 방법에 대한 연구가 필요하다. 본 연구팀은 이러한 위치인식의 요구사항을 만족시키기 위해 WSN(Wireless Sensor Network)을 이용한 위치인식 시스템을 제안한 바 있다. 하지만 기존 방법은 높은 효율성에 비해 위치인식의 정밀도가 낮은 단점이 있었다. 본 연구에서는 기존에 제안한 위치인식 프로토콜의 단점을 보완하기 위해 fingerprint 중첩을 사용하여 보다 높은 정밀도를 가지는 위치인식 방법을 제안한다. 기존 LIDx 프로토콜과 제안한 방법을 병행함으로써 효율적이면서도 정밀한 위치 인식형 서비스가 가능할 것으로 기대한다.

• Korean Security Journal
• /
• no.61
• /
• pp.377-400
• /
• 2019

Photography is the most commonly used method of documenting the crime and incident scene as it helps maintaining chain of custody (COC) and prove integrity of the physical evidence. It can also capture phenomena as they are. However, digital images can be manipulated and lose their authenticity as admissible evidence. Thus only limited techniques can be used to enhance images, and one of them is Fourier transform. Fourier transform refers to transformation of images into frequency signals. Fast Fourier transform (FFT) is used in this study. In this experiment, we overlapped fingerprints with graph paper or other fingerprints and separated the fingerprints. Then we evaluated and compared quality of the separated fingerprints to the original fingerprints, and examined whether the two fingerprints can be identified as same fingerprints. In the case of the fingerprints on graph paper and general pattern-overlapping fingerprints, fingerprint ridges are enhanced. On the other hand, in case of separating complicated fingerprints such as core-to-core overlapping and delta-to-delta overlapping fingerprints, quality of fingerprints can be deteriorated. Quality of fingerprints is known to possibly bring negative effects on the credibility of examiners. The result of this study may be applicable to other areas using digital imaging enhancement technology.

• 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 KIISE:Software and Applications
• /
• v.28 no.10
• /
• pp.764-772
• /
• 2001

This paper describes fingerprint matching algorithm using connected information between minutiae. We regard minutiae as ridge bifurcation and ridge ending. Features are composed of minutia's position, type(ridge bifurcation or ridge ending) ridge direction and connected ridge information. While the minutiae are extracted, we store connected in information between minutiae on the same ridge. They are used to find corresponding point pairs. Minutiae are aligned completely by two corresponding point pairs and point pattern matching is achieved by counting the number of overlapping pairs. It is invariable t translation and rotation. We have tested proposed method on the 445 fingerprints from 89 persons. These experimental results show that proposed algorithm improve 33% in speed.

• Journal of Plant Biotechnology
• /
• v.33 no.4
• /
• pp.277-281
• /
• 2006

Fourier transform - infrared spectroscopy (FT-IR) provides biochemical profiles containing overlapping signals from a majority of the compounds that are present when whole cell extracts are analyzed. We attempted to determine the ripeness of strawberry fruit flesh by FT-IR. Fruit ripeness was divided into four developmental stages based on fruit skin color: 'yellow-green', 'pink-green', 'pink', and 'red' stages. Principal component analysis of FT-IR data of inside fruit flesh extracts clustered samples of four different developmental stages into three discrete groups: (1) 'yellow-green' group, (2) 'pink-green' group, and (3) 'pink' and 'red' group. The most remarkable difference between four different developmental stages was found in the carbohydrate fingerprint region $(1,000-1,100cm^{-1})$ of the FT-IR spectrum, indicating that differences in carbohydrate compounds represented the ripeness of strawberry fruit. Overall results indicate that FT-IR in combination with PCA enables discrimination of the ripeness of strawberry fruit flesh.