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

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.45 no.5
• /
• pp.192-200
• /
• 2008

Multimodal biometrics is a method for personal authentication and verification using more than two types of biometrics data. RBF based score-level fusion uses pattern recognition algorithm for multimodal biometrics, seeking the optimal decision boundary to classify score feature vectors each of which consists of matching scores obtained from several unimodal biometrics system for each sample. In this case, all matching scores are assumed to have the same reliability. However, in recent research it is reported that the quality of input sample affects the result of biometrics. Currently the matching scores having low reliability caused by low quality of samples are not currently considered for pattern recognition modelling in multimodal biometrics. To solve this problem, in this paper, we proposed the RBF based score-level fusion approach which employs quality information of input biometrics data to adjust decision boundary. As a result the proposed method with Qualify information showed better recognition performance than both the unimodal biometrics and the usual RBF based score-level fusion without using quality information.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2017.04a
• /
• pp.837-840
• /
• 2017

각종 사이버 범죄가 증가함에 따라 실시간 모니터링을 통한 사전 탐지 기술뿐만 아니라, 사후 원인 분석을 통한 사고 재발 방지 기술의 중요성이 증가하고 있다. 사후 분석은 시스템에서 생산된 다양한 유형의 대용량 로그를 기반으로 분석가가 보안 위협 과정을 규명하는 것으로 이를 지원하는 다양한 상용 및 오픈 소스 SW 존재하나, 대부분 단일 분석가 PC에서 운용되는 파일 기반 SW로 대용량 데이터에 대한 분석 성능 저하, 다수 분석가 간의 데이터 공유 불가, 통계 연관 분석 한계 및 대화형 점진적 내용 분석 불가 등의 문제점을 해결하지 못하고 있다. 이러한 문제점을 해결하기 위하여 고성능 인메모리 관계형 데이터베이스 시스템을 로그 스토리지로 활용하는 대용량 로그 분석 SW 개발하였다. 특히, 기 확보된 공격자 프로파일을 활용하여 공격의 유무를 확인하는 텍스트 패턴 매칭 연산은 전통적인 관계형 데이터베이스 시스템의 FTS(Full-Text Search) 기능 활용이 가능하나, 대용량 전용 색인 생성에 따른 비현실적인 DB 구축 소요 시간과 최소 3배 이상의 DB 용량 증가로 인한 시스템 리소스 추가 요구 등의 단점이 있다. 본 논문에서는 인메모리 관계형 데이터베이스 시스템 기반 효율적인 텍스트 패턴 매칭 연산을 위하여, 고성능의 대용량 로그 DB 적재 방법과 새로운 유형의 패턴 매칭 방법을 제안하였다.

• Journal of KIISE:Databases
• /
• v.33 no.1
• /
• pp.42-55
• /
• 2006

We propose a single Index approach for subsequence matching that supports moving average transform of arbitrary order in time-series databases. Using the single index approach, we can reduce both storage space overhead and index maintenance overhead. Moving average transform is known to reduce the effect of noise and has been used in many areas such as econometrics since it is useful in finding overall trends. However, the previous research results have a problem of occurring index overhead both in storage space and in update maintenance since tile methods build several indexes to support arbitrary orders. In this paper, we first propose the concept of poly-order moving average transform, which uses a set of order values rather than one order value, by extending the original definition of moving average transform. That is, the poly-order transform makes a set of transformed windows from each original window since it transforms each window not for just one order value but for a set of order values. We then present theorems to formally prove the correctness of the poly-order transform based subsequence matching methods. Moreover, we propose two different subsequence matching methods supporting moving average transform of arbitrary order by applying the poly-order transform to the previous subsequence matching methods. Experimental results show that, for all the cases, the proposed methods improve performance significantly over the sequential scan. For real stock data, the proposed methods improve average performance by 22.4${\~}$33.8 times over the sequential scan. And, when comparing with the cases of building each index for all moving average orders, the proposed methods reduce the storage space required for indexes significantly by sacrificing only a little performance degradation(when we use 7 orders, the methods reduce the space by up to 1/7.0 while the performance degradation is only $9\%{\~}42\%$ on the average). In addition to the superiority in performance, index space, and index maintenance, the proposed methods have an advantage of being generalized to many sorts of other transforms including moving average transform. Therefore, we believe that our work can be widely and practically used in many sort of transform based subsequence matching methods.

• Journal of Korean Society for Geospatial Information Science
• /
• v.24 no.1
• /
• pp.89-98
• /
• 2016

In this paper, we proposed an automated areal feature matching method based on geometric similarity without user intervention and is applied into areal features of many-to-many relation, for confusion of spatial data-sets of different scale and updating cycle. Firstly, areal feature(node) that a value of inclusion function is more than 0.4 was connected as an edge in adjacency matrix and candidate corresponding areal features included many-to-many relation was identified by multiplication of adjacency matrix. For geometrical matching, these multiple candidates corresponding areal features were transformed into an aggregated polygon as a convex hull generated by a curve-fitting algorithm. Secondly, we defined matching criteria to measure geometrical quality, and these criteria were changed into normalized values, similarity, by similarity function. Next, shape similarity is defined as a weighted linear combination of these similarities and weights which are calculated by Criteria Importance Through Intercriteria Correlation(CRITIC) method. Finally, in training data, we identified Equal Error Rate(EER) which is trade-off value in a plot of precision versus recall for all threshold values(PR curve) as a threshold and decided if these candidate pairs are corresponding pairs or not. To the result of applying the proposed method in a digital topographic map and a base map of address system(KAIS), we confirmed that some many-to-many areal features were mis-detected in visual evaluation and precision, recall and F-Measure was highly 0.951, 0.906, 0.928, respectively in statistical evaluation. These means that accuracy of the automated matching between different spatial data-sets by the proposed method is highly. However, we should do a research on an inclusion function and a detail matching criterion to exactly quantify many-to-many areal features in future.

• The KIPS Transactions:PartD
• /
• v.11D no.5
• /
• pp.1003-1010
• /
• 2004

In this paper, we address efficient processing of subsequence matching in time-series databases. We first point out the performance problems occurring in the index searching of a prior method for subsequence matching. Then, we propose a new method that resolves these problems. Our method starts with viewing the index searching of subsequence matching from a new angle, thereby regarding it as a kind of a spatial-join called a window-join. For speeding up the window-join, our method builds an R＊-tree in main memory for f query sequence at starting of sub-sequence matching. Our method also includes a novel algorithm for joining effectively one R＊-tree in disk, which is for data sequences, and another R＊-tree in main memory, which is for a query sequence. This algorithm accesses each R＊-tree page built on data sequences exactly cure without incurring any index-level false alarms. Therefore, in terms of the number of disk accesses, the proposed algorithm proves to be optimal. Also, performance evaluation through extensive experiments shows the superiority of our method quantitatively.

• The KIPS Transactions:PartD
• /
• v.15D no.1
• /
• pp.31-40
• /
• 2008

We generally use lower-dimensional transformations to convert high-dimensional sequences into low-dimensional points in similar sequence matching. These traditional transformations, however, show different characteristics in indexing performance by the type of time-series data. It means that the selection of lower-dimensional transformations makes a significant influence on the indexing performance in similar sequence matching. To solve this problem, in this paper we propose a hybrid approach that integrates multiple transformations and uses them in a single multidimensional index. We first propose a new notion of hybrid lower-dimensional transformation that exploits different lower-dimensional transformations for a sequence. We next define the hybrid distance to compute the distance between the transformed sequences. We then formally prove that the hybrid approach performs the similar sequence matching correctly. We also present the index building and the similar sequence matching algorithms that use the hybrid approach. Experimental results for various time-series data sets show that our hybrid approach outperforms the single transformation-based approach. These results indicate that the hybrid approach can be widely used for various time-series data with different characteristics.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.23 no.11
• /
• pp.1343-1350
• /
• 2019

Converting boundary images to time-series makes it feasible to perform boundary matching even on a very large image database, which is very important for interactive and fast matching. In recent research, there has been an attempt to perform fast matching considering partial denoising by converting the boundary image into time series. In this paper, to improve performance, we propose an index-building method considering all possible arbitrary denoising parameters for removing arbitrary partial noises. This is a challenging problem since the partial denoising boundary matching must be considered for all possible denoising parameters. We propose an efficient single index-building algorithm by constructing a minimum bounding rectangle(MBR) according to all possible denoising parameters. The results of extensive experiments conducted show that our index-based matching method improves the search performance up to 46.6 ~ 4023.6 times.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.45 no.2
• /
• pp.26-36
• /
• 2008

Due to the differential and low voltage swing, Low Voltage Differential Signaling(LVDS) has been widely used for high speed data transmission with low power consumption. This paper proposes new LVDS I/O interface circuits for more than 1.3 Gb/s operation. The LVDS receiver proposed in this paper utilizes a sense amp for the pre-amp instead of a conventional differential pre-amp. The proposed LVDS allows more than 1.3 Gb/s transmission speed with significantly reduced driver output voltage. Also, in order to further improve the power consumption and noise performance, this paper introduces an inductance impedance matching technique which can eliminate the termination resistor. A new form of unfolded impedance matching method has been developed to accomplish the impedance matching for LVDS receivers with a sense amplifier as well as with a differential amplifier. The proposed LVDS I/O circuits have been extensively simulated using HSPICE based on 0.35um TSMC CMOS technology. The simulation results show improved power gain and transmission rate by ${\sim}12%$ and ${\sim}18%$, respectively.

• Journal of Advanced Marine Engineering and Technology
• /
• v.39 no.6
• /
• pp.626-632
• /
• 2015

The International Maritime Organization (IMO) has adopted several regulations for the prevention of air pollution from ships. In addition, there is a requirement for shipping liners to reduce greenhouse gas emissions. Accordingly, we need to take measurements to ensure that the steps taken are both efficient and environmentally friendly. It has been determined that the application of the Miller cycle in diesel engines has the effect of both reducing the amount of NOx and improving thermal efficiency. However, this method requires a considerably larger charge air pressure. Therefore, we consider a two-stage turbo-charging system, which not only results in a high charging pressure, but also improves the part load performance with an exhaust-gas bypass system or the application of the Miller cycle. Because of complications associated with the two-stage turbo-charging system, it is complex and difficult to realize a design that optimizes matching between diesel engine and turbo-chargers. Accordingly, it is necessary to perform a quantitative analysis to determine the effects and optimal conditions of these different systems in the early stage of system design. In this paper, we develop a simulation program to model these systems, and we verify that the results of this program are reliable. Further, we discuss methods that can be employed to improve its efficiency.