• The Transactions of the Korean Institute of Electrical Engineers
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• v.35 no.3
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• pp.87-94
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• 1986

This paper introduce a new test generation method based on built-in data base which is suitable for generating of test set by using PROLOG language. The program presented in this paper deals with all the information required for fault detection from the rules describing output signals and internal signals. Example shows the validity of proposed PROLOG program which results in a effective generation of test set comparable to the conventional D-algorithm.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.633-636
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• 1999

We present a robust scheme of detecting obstacles such as vehicles, human beings, and other artificial structures that may cause serious traffic accidents in the nighttime driving. Obstacle regions are detected by the evidential reasoning rules that combine the isolated regions obtained by the phase-directed edge-linking and the hot evidence information. Preliminary experimental results show that the performance is robust to nighttime infrared scenes having various types of obstacles

• Proceedings of the Korean Information Science Society Conference
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• 2003.10a
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• pp.706-708
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• 2003

침입탐지 시스템 중 하나인 오용탐지 시스템은 축적된 침입패턴 정보를 이용하기 때문에 새로운 침입에 대하여 새로운 정의가 필요하다. 이러한 문제점을 극복하여 새로운 침입에 대하여 일일이 정의하지 않고 자동으로 새로운 규칙을 생성하도록 하는 것이 좀 더 바람직하다. 본 논문에서는 새로운 규칙을 찾기 위한 방법으로 생물의 진화과정을 모델링한 유전자 알고리즘(GA)을 이용하였다. GA는 계산에 의존한 방법에 비하여 전역적인 해를 구할 때 더 효율적이다. GA를 이용하여 규칙을 자동 생성하고 침입을 탐지할 수 있는 규칙을 찾아가는 방식을 제안하였다. 실험 결과에서는 GA를 이용하여 자동 생성된 규칙으로 40~60%의 탐지율로 침입을 탐지할 수 있다는 것을 확인하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.05a
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• pp.155-160
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• 2003

This paper presents a multiple face detector based on a robust pupil detection technique. The pupil detector uses active illumination that exploits the retro-reflectivity property of eyes to facilitate detection. The detection range of this method is appropriate for interactive desktop and kiosk applications. Once the location of the pupil candidates are computed, the candidates are filtered and grouped into pairs that correspond to faces using heuristic rules. To demonstrate the robustness of the face detection technique, a dual mode face tracker was developed, which is initialized with the most salient detected face. Recursive estimators are used to guarantee the stability of the process and combine the measurements from the multi-face detector and a feature correlation tracker. The estimated position of the face is used to control a pan-tilt servo mechanism in real-time, that moves the camera to keep the tracked face always centered in the image.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.7
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• pp.350-356
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• 2017

With increasing attention to real-time body detection, active research is being conducted on human body detection based on skin color. Despite this, most existing skin detection methods utilize static skin color models and have detection rates in images, in which colors are distorted. This study proposed a method of detecting the skin region using a fuzzy classification of the gradient map, saturation, and Cb and Cr in the YCbCr space. The proposed method, first, creates a gradient map, followed by a saturation map, CbCR map, fuzzy classification, and skin region binarization in that order. The focus of this method is to rigorously detect human skin regardless of the lighting, race, age, and individual differences, using features other than color. On the other hand,the borders between these features and non-skin regions are unclear. To solve this problem, the membership functions were defined by analyzing the relationship between the gradient, saturation, and color features and generate 108 fuzzy rules. The detection accuracy of the proposed method was 86.35%, which is 2~5% better than the conventional method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.8
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• pp.1823-1830
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• 2003

This paper presents a multiple face detector based on a robust pupil detection technique. The pupil detector uses active illumination that exploits the retro­reflectivity property of eyes to facilitate detection. The detection range of this method is appropriate for interactive desktop and kiosk applications. Once the location of the pupil candidates are computed, the candidates are filtered and grouped into pairs that correspond to faces using heuristic rules. To demonstrate the robustness of the face detection technique, a dual mode face tracker was developed, which is initialized with the most salient detected face. Recursive estimators are used to guarantee the stability of the process and combine the measurements from the multi­face detector and a feature correlation tracker. The estimated position of the face is used to control a pan­tilt servo mechanism in real­time, that moves the camera to keep the tracked face always centered in the image.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1315-1318
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• 2004

Based on fuzzy 2-mean classification and template matching method, we propose a new algorithm to detect the edges of an image. In the algorithm, fuzzy 2-mean classification can classify all pixels in the mask into two clusters whatever the mask in the dark or light region; and template matching not only determines the edge's direction, but also thins the detected edge by a set of inference rules and, by the way, reduces the impulse noises.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.224-227
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• 2003

The Intrsuion Detecion Systems(IDS) are required the accuracy, the adaptability, and the expansion in the information society to be changed quickly. Also, it is required the more structured, and intelligent IDS to protect the resource which is important and maintains a secret in the complicated network environment. The research has the purpose to build the model for the intelligent IDS, which creates the intrusion patterns. The intrusion pattern has extracted from the vast amount of data. To manage the large size of data accurately and efficiently, the link analysis and sequence analysis among the data mining techniqes are used to build the model creating the intrusion patterns. The model is consist of "Time based Traffic Model", "Host based Traffic Model", and "Content Model", which is produced the different intrusion patterns with each model. The model can be created the stable patterns efficiently. That is, we can build the intrusion detection model based on the intelligent systems. The rules prodeuced by the model become the rule to be represented the intrusion data, and classify the normal and abnormal users. The data to be used are KDD audit data.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.11
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• pp.126-133
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• 2007

Tuberculosis (TB) is a chronic or acute infectious disease which damages more people than any other infectious diseases according to WHO estimates. In this paper, a new automatic detection system of tuberculosis bacilli by using their color information is proposed. Through the deep investigation of color and intensity compositions of tuberculosis images, new pre-processing and segmentation algorithms are suggested. Specific features of bacilli are extracted from the processed images and number counting is done by using domain-specific knowledge rules.

• Journal of Korea Multimedia Society
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• v.23 no.1
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• pp.24-30
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• 2020

As the number of internet-connected appliances and the variety of IoT services are rapidly increasing, it is hard to protect IT assets with traditional network security techniques. Most traditional network log analysis systems use rule based mechanisms to reduce the raw logs. But using predefined rules can't detect new attack patterns. So, there is a need for a mechanism to reduce congested raw logs and detect new attack patterns. This paper suggests enterprise security management for IoT services using graph and network measures. We model an event network based on a graph of interconnected logs between network devices and IoT gateways. And we suggest a network clustering algorithm that estimates the attack probability of log clusters and detects new attack patterns.