• 한국항행학회논문지
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• 제15권5호
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• pp.696-704
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• 2011

본 논문에서는 단일 카메라와 초음파센서 데이터를 융합하는 이동 로봇 주행제어 알고리즘을 제안하였다. 이진화 영상처리를 위한 임계값을 영상 정보와 초음파센서 정보를 이용하는 퍼지추론기법으로 설정하였다. 임계값을 상황에 따라 가변하면 조도가 낮은 환경에서도 장애물 인식이 향상된다. 카메라 영상 정보와 초음파 센서 정보를 융합하여 장애물에 대한 격자지도를 생성하고 원궤적 경로기법으로 장애물을 회피하도록 한다. 제안된 알고리즘의 성능을 입증하기 위하여 조도가 낮은 실내와 좁은 복도에서 Pioneer 2-DX 이동로봇의 주행제어에 적용하였다.

• 한국정보통신학회논문지
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• 제9권2호
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• pp.462-466
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• 2005

운송 컨테이너 영상으로부터 식별자를 추출하고 인식하는 것은 컨테이너 식별자들의 크기나 위치가 정형화되어 있지 않고 외부의 잡음으로 인하여 식별자의 형태가 훼손되어 있기 때문에 어렵다. 본 논문에서는 이러한 특성을 고려하여 컨테이너 영상에 대해 Canny 마스크를 이용하여 에지를 검출하고, Canny 마스크가 적용된 영상에서 수직 수평 히스토그램을 적용하여 컨테이너의 식별자 영역을 추출한다 추출된 컨테이너의 식별자 영역을 퍼지 이진화 방법을 적용하여 이진화하고, 이진화된 컨테이너 식별자 영역을 윤곽선 추적 알고리즘으로 개별 식별자를 추출한다. 제안된 방법의 성능을 평가하기 위하여 실제 컨테이너 영상에 적용한 결과, 제안된 추출 방법이 컨테이너의 식별자 추출에 효율적인 것을 확인하였다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 하계종합학술대회 논문집
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• pp.583-586
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• 1999

In this paper, the wavelet transform is performed in the input 256$\times$256 color image and decomposes a image into low-pass and high-pass components. Since the high-pass band contains the components of three directions, edges are detected by combining three parts. After finding the position of face using the histogram of the edge component, a face region in low-pass band is cut off. Since RGB color image is sensitively affected by luminances, the image of low pass component is normalized, and a facial region is detected using face color informations. As the wavelet transform decomposes the detected face region into three layer, the dimension of input image is reduced. In this paper, we use the 3000 images of 10 persons, and KL transform is applied in order to classify face vectors effectively. FCM(Fuzzy C-Means) algorithm classifies face vectors with similar features into the same cluster. In this case, the number of cluster is equal to that of person, and the mean vector of each cluster is used as a codebook. We verify the system performance of the proposed algorithm by the experiments. The recognition rates of learning images and testing image is computed using correlation coefficient and Euclidean distance.

• 제어로봇시스템학회논문지
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• 제15권1호
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• pp.94-98
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• 2009

In this paper, we deal with a face recognition method for the emotional face images. Since the face recognition is one of the most natural and straightforward biometric methods, there have been various research works. However, most of them are focused on the expressionless face images and have had a very difficult problem if we consider the facial expression. In real situations, however, it is required to consider the emotional face images. Here, three basic human emotions such as happiness, sadness, and anger are investigated for the face recognition. And, this situation requires a robust face recognition algorithm then we use a fuzzy Fisher's Linear Discriminant (FLD) algorithm with the wavelet transform. The fuzzy Fisherface is a statistical method that maximizes the ratio of between-scatter matrix and within-scatter matrix and also handles the fuzzy class information. The experimental results obtained for the CBNU face databases reveal that the approach presented in this paper yields better recognition performance in comparison with the results obtained by other recognition methods.

• 대한기계학회논문집A
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• 제25권2호
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• pp.323-329
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• 2001

In this paper, we present a collaborative method for material delivery using a distributed vehicle agents system. Generally used AGV(Autonomous Guided Vehicle) systems in FA require extraordinary facilities like guidepaths and landmarks and have numerous limitations for application in different environments. Moreover in the case of controlling multi vehicles, the necessity for developing corporation abilities like loading and unloading materials between vehicles including different types is increasing nowadays for automation of material flow. Thus to compensate and improve the functions of AGV, it is important to endow vehicles with the intelligence to recognize environments and goods and to determine the goal point to approach. In this study we propose an interaction method between hetero-type vehicles and adaptive fuzzy logic controllers for sensor-based path planning methods and material identifying methods which recognizes color. For the purpose of carrying materials to the goal, simple color sensor is used instead vision system to search for material and recognize its color in order to determine the goal point to transfer it to. The proposed method reaveals a great deal of improvement on its performance.

• 디지털산업정보학회논문지
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• 제13권3호
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• pp.19-25
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• 2017

Nowadays, networked computer systems play an increasingly important role in our society and its economy. They have become the targets of a wide array of malicious attacks that invariably turn into actual intrusions. This is the reason computer security has become an essential concern for network administrators. Recently, a number of Detection/Prevention System schemes have been proposed based on various technologies. However, the techniques, which have been applied in many systems, are useful only for the existing patterns of intrusion. Therefore, probe detection has become a major security protection technology to detection potential attacks. Probe detection needs to take into account a variety of factors ant the relationship between the various factors to reduce false negative & positive error. It is necessary to develop new technology of probe detection that can find new pattern of probe. In this paper, we propose an hybrid probe detection using Fuzzy Cognitive Map(FCM) and Self Adaptive Module(SAM) in dynamic environment such as Cloud and IoT. Also, in order to verify the proposed method, experiments about measuring detection rate in dynamic environments and possibility of countermeasure against intrusion were performed. From experimental results, decrease of false detection and the possibilities of countermeasures against intrusions were confirmed.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2001년도 춘계학술대회 학술발표 논문집
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• pp.136-139
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• 2001

This paper develops a sensor based navigation method that utilizes fuzzy logic and the Dempster-Shafer evidence theory for mobile robot in uncertain environment. The proposed navigator consists of two behaviors: obstacle avoidance and goal seeking. To navigate reliably in the environment, we make a map building process before the robot finds a goal position and create a robust fuzzy controller. In this paper, the map is constructed on a two-dimensional occupancy grid. The sensor readings are fused into the map using D-S inference rule. Whenever the robot moves, it catches new information about the environment and replaces the old map with new one. With that process the robot can go wandering and finding the goal position. The usefulness of the proposed method is verified by a series of simulations. This paper deals with the fuzzy modeling for the complex and uncertain nonlinear systems, in which conventional and mathematical models may fail to give satisfactory results. Finally, we provide numerical examples to evaluate the feasibility and generality of the proposed method in this paper.

• 산업경영시스템학회지
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• 제30권1호
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• pp.89-95
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• 2007

In general, reliability of AHP(Analytic Hierarchy Process) depends on pairwise comparison of evaluators. In addition, human judgment on the importance of alternatives or criteria is always imprecise and vague. To cope with these shortcomings, Fuzzy AHP is suggested and used widely recently. But in Fuzzy AHP, it cannot deal with the evaluator's various attitudes towards risk and confidence owing to evaluator's different expertise and experience. This paper proposes a method for consideration of evaluator's confidence and risk attitude in Fuzzy AHP. And suggested methods are applied various scenarios to verify the meaningfulness. The result shows that the priority of alternatives can be change through the consideration of evaluator's confidence and risk attitude.

• 대한기계학회논문집A
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• 제28권2호
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• pp.125-132
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• 2004

In this paper, we propose a new two-stage segmentation method for the effective object recognition which uses region-growing algorithm and k-means clustering method. At first, an image is segmented into many small regions via region growing algorithm. And then the segmented small regions are merged in several regions so that the regions of an object may be included in the same region using typical k-means clustering method. This paper also establishes similarity measurement which is useful for object recognition in an image. Similarity is measured by fuzzy system whose input variables are compactness, magnitude of biasness and orientation of biasness of the object image, which are geometrical features of the object. To verify the effectiveness of the proposed two-stage segmentation method and similarity measurement, experiments for object recognition were made and the results show that they are applicable to object recognition under normal circumstance as well as under abnormal circumstance of being.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2009년도 춘계학술대회
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• pp.373-376
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• 2009

영상처리 기술은 인간의 시각에 기반을 둔 영상정보와 관련된 분야에서 중요한 기반 기술로써 현재 여러 분야에서 연구가 활발하게 진행 중이다. 여러 응용 분야에서 사용되는 영상처리의 세부 기술범위는 영상 변환, 영상 개선, 영상 복원, 영상 압축등과 같이 다양하며, 이런 영상처리 기술의 중요한 연구 목표 중의 하나는 정확한 정보 추출을 위한 영상정보의 개선에 있다. 영상정보의 개선은 영상의 해석과 인식을 위한 기본적인 과제이며, 영상에서 나타날 수 있는 잡음을 제거하는 영상처리 기술이 영상정보 개선의 한 분야라고 할 수 있다. 영상정보 개선을 위한 기존의 필터링 알고리즘은 잡음제거율이 높은 만큼 경계선의 보존이 어렵다는 단점이 있으며, 이를 보완하기 위해 다른 영상처리 알고리즘을 함께 응용하여 처리함으로써 처리시간이 증가되고 원 영상의 중요한 정보를 훼손할 가능성이 존재한다. 따라서 본 논문에서는 기존의 필터링 알고리즘의 문제점을 개선하는 동시에 잡음 제거율을 높일 수 있는 Fuzzy Mask Filter 알고리즘을 제안한다. Fuzzy Mask Filter 알고리즘은 마스크에서 얻은 정보를 Fuzzy Logic에 적용하여 임계값을 구하며, 구해진 임계값을 기준으로 출력영상의 화소값을 결정하는 알고리즘이다. 본 논문에서 제안한 알고리즘의 효율성을 검증하기 위해 Impulse 잡음과 Salt pepper 잡음을 임의로 생성하여 기존의 알고리즘과 비교한 결과, 제안된 방법이 잡음 영상에 존재하는 픽셀 정보를 훼손하지 않고 잡음을 효과적으로 제거한 것을 확인할 수 있었다.