• Proceedings of the Korean Information Science Society Conference
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• 2001.10a
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• pp.640-642
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• 2001

침입 탐지 시스템의 초점이 호스트와 운영체제 탐지에서 네트워크 탐지로 옮겨가고 있고 단순만 오용 탐지 기법에서 이를 개선한 지능적인 비정상 행위 탐지 기법에 관한 연구들이 진행되고 있다. 이러한 연구들 중에는 네트워크 프로토콜의 트래픽 특성을 이용하여 비표준 포트의 사용이나 표준 포트에 대한 비표준 방법에 의한 침입을 탐지하고자 하는 노력도 있다. 본 연구에서는 실시간으로 패턴 매칭이 가능하고, 적응력이 뛰어난 신경망 알고리즘을 이용하여 네트워크 서비스들에 대한 트래픽을 수집, 특성에 따라 분석.클러스터링하고 그 결과를 바탕으로 보다 향상된 침입 탐지가 가능한 시스템을 제안한다.

• Journal of Industrial Technology
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• v.21 no.B
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• pp.67-74
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• 2001

According as the patterns of PCB (Printed Circuit Board) become denser and complicated, quality and accuracy of PCB influence the performance of final product. It's attempted to obtain trust of 100% about all of parts. Because human inspection in mass-production manufacturing facilities are both time-consuming and very expensive, the automation of visual inspection has been attempted for many years. Thus, automatic visual inspection of PCB is required. In this paper, we used an algorithm which compares the reference PCB patterns and the input PCB patterns are separated an object and a scene by filtering and edge detection. And than compare two image using pattern matching algorithm. We suggest an defect inspection algorithm in PCB pattern, to be satisfied low cost, high speed, high performance and flexibility on the basis of $640{\times}480$ binary pattern.

• Proceedings of the Korean Society of Computer Information Conference
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• 2011.01a
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• pp.65-68
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• 2011

이 논문에서는 모래의 주성분을 분석하여 콘크리트 배합설계용의 적합성을 판별하는 시험방법을 제안한다. 주성분을 분석하는 방법은 자연모래와 부순 모래, 그리고 혼합모래에 포함된 유해물(점토, 마사토, 염화물)의 패턴을 분석하여 정지영상에서 유해물 비율을 나타내고자 한다. 영상으로 판독된 유해물 비율은 도로공사 품질시험기준에 의해 시험된 데이터와 비교하여 근접한 값을 도출해 내어 건설 자재인 모래에 섞여있는 유해물질을 검출해 내는 알고리즘을 제시한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.399-400
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• 2009

무마커 기반 증강현실 응용에서 빠르고 정확한 무마커 추적이 수행되어야 한다. 무마커 추적은 등록된 패턴의 특징점들과 입력 영상에서의 특징점들의 매칭을 통하여 수행된다. 매칭에서 이상점은 시차를 크게 유발시키는 요인이 되므로 정확도 향상을 위해서는 이상점을 제거해야 한다. 본 논문에서는 무마커 추적의 정확도 향상을 위한 이상점 제거 방식을 제안한다. 무마커 추적에서 사용되는 SURF 알고리즘을 사용하여 실영상을 캡처하여 실험하였고 정확도 및 실행시간을 비교하였다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.4
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• pp.53-57
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• 2009

In this paper to computerized patient management of patients applying for a facial recognition algorithm to extract Face Feature Points environment, the implementation of the U-Healthcare offers. First, mobile devices and the pictures and photos of the patient data used as input data, the algorithm AdaBoost Face Feature Points patterns extracted, then stored in an existing database, extracted from the patient's sample photos, matching patterns and makes Face Feature Points. The result is the same patient if the patient information database, in recognizing the disease, doctors, and medical fields to extract the relevant information on the screen to output devices, the patient will present the implementation of recognition system.

• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.89-97
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• 2023

In this paper, we propose factors that make log analysis difficult and design technique for detecting various objects embedded in the logs which helps in the subsequent analysis. In today's IT systems, logs have become a critical source data for many advanced AI analysis techniques. Although logs contain wealth of useful information, it is difficult to directly apply techniques since logs are semi-structured by nature. The factors that interfere with log analysis are various objects such as file path, identifiers, JSON documents, etc. We have designed a BERT-based object pattern recognition algorithm for these objects and performed object identification. Object pattern recognition algorithms are based on object definition, GROK pattern, and regular expression. We find that simple pattern matchings based on known patterns and regular expressions are ineffective. The results show significantly better accuracy than using only the patterns and regular expressions. In addition, in the case of the BERT model, the accuracy of classifying objects reached as high as 99%.

• KIISE Transactions on Computing Practices
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• v.21 no.2
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• pp.138-143
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• 2015

The Boyer-Moore algorithm is a single pattern string matching algorithm that is widely used in various applications such as computer and internet security, and bioinformatics. This algorithm is computationally demanding and requires high-performance parallel processing. In this paper, we propose a parallelization and performance optimization methodology for the BM algorithm on a GPU. Our methodology adopts an algorithmic cascading technique. This results in significant reductions in the mapping overheads for the threads participating in the parallel string matching. It also results in the efficient utilization of the multithreading capability of the GPU which improves the load balancing among threads. Our experimental results show that this approach achieves a 45-times speedup at maximum, in comparison with a serial execution.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.1
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• pp.107-114
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• 2017

Iris diagnosis is an alternative medicine to diagnose the disease of the patient by using different of the iris pattern, color and other characteristics. This paper proposed a disease prediction algorithm that using the iris regions that analyze iris change to using differential image of iris image. this method utilize as patient's health examination according to iris change. Because most of previous studies only find a sign pattern in a iris image, it's not enough to be used for a iris diagnosis system. We're developed an iris diagnosis system based on a iris images processing approach, It's presents the extraction algorithms of 8 major iris signs and correction manually for improving the accuracy of analysis. As a result, PNSR of applied edge detection image is about 132, and pattern matching area recognition presented practical use possibility by automatic diagnostic that presume situation of human body by iris about 91%.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.6
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• pp.58-67
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• 2009

A correspondence matching is one of the important tasks in computer vision, and it is not easy to find corresponding points in variable environment where a scale, rotation, view point and illumination are changed. A SURF(Speeded Up Robust Features) algorithm have been widely used to solve the problem of the correspondence matching because it is faster than SIFT(Scale Invariant Feature Transform) with closely maintaining the matching performance. However, because SURF considers only gray image and local geometric information, it is difficult to match corresponding points on the image where similar local patterns are scattered. In order to solve this problem, this paper proposes an extended SURF algorithm that uses the invariant color and global geometric information. The proposed algorithm can improves the matching performance since the color information and global geometric information is used to discriminate similar patterns. In this paper, the superiority of the proposed algorithm is proved by experiments that it is compared with conventional methods on the image where an illumination and a view point are changed and similar patterns exist.

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