• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.3
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• pp.558-566
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• 2015

LED, the next-generation light source, rapidly develops and has advantages of low power, high efficiency, and long life. Accordingly, an interest in lightings by using LED rises. If emotional lighting is implemented by using LED, all colors can be represented by using 3 primary colors of light, differently from the conventional single-color lighting. LED emotional lightings which can control human emotions continue to be developed thanks to these advantages. This study was conducted to design an algorithm for expressing LED emotional lighting in line with the situation and temperature by extracting colors for concentration and resting situations in indoor environment and mixing them with colors of the temperature felt by user. The LED emotional lighting designed with a neuro-fuzzy system was found to have effects on user's emotions during concentration and resting.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.4
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• pp.9-17
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• 1997

This paper describes a monitoring system that examines water quality by analyzing behavioral patterns of fishes. The water quality inspection system (WQIS) captures color images of fishes with a CCD camera, extracts out fish regions from the images, and determines motion characteristics of fishes by computing consecutive frames. We define five types of measures that reflect behavioral patterns of fishes : floatness, fledness, clustemess, diffusiveness, and mobility. These measures are utilized when the system performs fuzzy inference to induce the conclusion about water quality. We believe that the proposed system can be a solution for securing clean water.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.01a
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• pp.47-50
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• 2018

본 논문에서는 초음파 영상에서 환자 정보를 제거하여 ROI 영역을 추출하고, 추출된 ROI 영역에서 최대 명암도를 임계치로 설정한 이진화 기법을 적용하여 ROI 영역을 이진화 한다. 이진화된 ROI 영역에서 4 방향 윤곽선 추적 기법을 적용하여 상완동맥 혈류 영역이 존재하는 사다리꼴 형태의 영역을 추출한다. 추출된 사다리꼴 형태의 영역에서 상완동맥 혈류영역을 정확히 추출하기 위하여 제안된 무게 중심법을 이용하여 추출된 후보 영역을 양자화 한다. 무게 중심법은 추출된 사다리꼴 영역에서 FCM 기반 무게중심법과 PCM 기반 무게중심법을 각각 계산한 후, 두 중심 간의 차이가 존재 할 경우에는 두 중심의 평균값을 새로운 무게 중심으로 설정하여 각 픽셀들을 클러스터링하여 상완 동맥 영역을 추출한다. 추출된 상완 동맥 영역에는 고혈압 영역인 빨강색 영역과 저혈압이나 혈류가 역류하는 영역인 파란색 영역이 존재한다. 추출된 상완 동맥 영역에서 고혈압 영역만을 추출하기 위해 빨강색 영역을 제외한 그 외의 영역은 제거한다. 전문의가 제공한 상완동맥 혈류 초음파 영상을 대상으로 TPR(True Positive Rate) 검사을 분석한 결과, 제안된 방법이 기존의 방법 보다 TPR 값이 높게 나타나는 것을 확인하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.10
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• pp.2201-2206
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• 2010

The shortage of fossil fuel drives researchers to find a new way to increases energy efficiency. In this paper, we propose a method to control the direction and speed of an air conditioner using a thermal image and fuzzy controlling method, which results in the increase of energy efficiency. The thermal image is first converted into a color temperature image which represents the temperature range from $24.0^{\circ}C$ to $27.0^{\circ}C$. The temperature image is divided into 5 columns and the distribution of them is used to analyze room temperature and control an air conditioner. The proposed method was applied to 300 by 400 thermal images. When the performance of the proposed method was compared to existing systems in energy efficiency, the proposed method was better than existing methods, which is clear from experimental results.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.42 no.4
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• pp.15-20
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• 2005

If we can forecast the replacement time of engine oil, we extend the life-time of our engine and increase the continued ratio. But, the replacement times of engine oil is influenced by the following elements: the distance that cars or vehicles travel, vehicles that run a short range, types of engine oil etc. that run a long distance. In this paper, We forecast engine oil replacement times by using fuzzy neural network algorithm. This algerian uses the data of distance covered, color of engine oil etc. Through a sequence of simulation, the exchange system of intelligence style engine oil decides on the replacement times of engine oil quite accurately. Therefore, We expect vehicles to become more convenient if the above algorithm is a lied to the present types of cars.

• Journal of the Korea Society of Computer and Information
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• v.13 no.6
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• pp.273-278
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• 2008

Cars attaching new license plates are increasing after introducing the new format of car license plate in Korea. Therefore, a car new license plate recognition system is required for various fields using automatic recognition of car license plates, automatic parking management systems and arrest of criminal or missing vehicles. In this paper, we proposed an intelligent new car license plate recognition method for the various fields. The proposed method is as follows. First of all, an acquired color image from a surveillance camera is converted to a gray level image and binarized by block binarization method. Second, noises of the binarized image removed by morphological characteristics of cars and then license plate area is extracted. Third, individual characters are extracted from the extracted license plate area using Grassfire algorithm. lastly, the extracted characters are learned and recognized by a fuzzy ART algorithm for final car license plate recognition. In the experiment using 100 car images, we could see that the proposed method is efficient.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.6 s.312
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• pp.20-27
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• 2006

Multi-level thresholding is a method that is widely used in image segmentation. However most of the existing methods are not suited to be directly used in applicable fields and moreover expanded until a step of image segmentation. This paper proposes region-based multi-level thresholding as an image segmentation method. At first we classify pixels of each color channel to two clusters by using EWFCM(Entropy-based Weighted Fuzzy C-Means) algorithm that is an improved FCM algorithm with spatial information between pixels. To obtain better segmentation results, a reduction of clusters is then performed by a region-based reclassification step based on a similarity between regions existing in a cluster and the other clusters. The clusters are created using the classification information of pixels according to color channel. We finally perform a region merging by Bayesian algorithm based on Kullback-Leibler distance between a region and the neighboring regions as a post-processing method as many regions still exist in image. Experiments show that region-based multi-level thresholding is superior to cluster-, pixel-based multi-level thresholding, and the existing mettled. And much better segmentation results are obtained by the post-processing method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.488-491
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• 2005

This paper has been proposed an engine oil changing system automatically using artificial intelligence. As you know, It is very difficult to forecast the time that exchange engine oil exactly. Because, It does not necessary to change the engine oil when color of engine is black or distance is more than 3000 km. In order to forecast to optimal engine oil replacement time, We must to consider color of engine oil, greasy, mad condition, quick starting condition and quick braking condition. Therefore, in this paper, to overcome those problems, we, developed an expert system that it can forecast to exchange time of engine oil automatically using fuzzy rules and neural networks.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.165-171
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• 2004

Robots will be able to coexist with humans and support humans effectively in near future. One of the most important aspects in the development of human-friendly robots is to cooperation between humans and robots. In this paper, we proposed a method for multi-object identification in order to achieve such human-centered system and robot localization in intelligent space. The intelligent space is the space where many intelligent devices, such as computers and sensors, are distributed. The Intelligent Space achieves the human centered services by accelerating the physical and psychological interaction between humans and intelligent devices. As an intelligent device of the Intelligent Space, a color CCD camera module, which includes processing and networking part, has been chosen. The Intelligent Space requires functions of identifying and tracking the multiple objects to realize appropriate services to users under the multi-camera environments. In order to achieve seamless tracking and location estimation many camera modules are distributed. They causes some errors about object identification among different camera modules. This paper describes appearance based object representation for the distributed vision system in Intelligent Space to achieve consistent labeling of all objects. Then, we discuss how to learn the object color appearance model and how to achieve the multi-object tracking under occlusions.

• Journal of Biosystems Engineering
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• v.30 no.6 s.113
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• pp.340-346
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• 2005

Major quality features of the beef carcass in most countries including Korea are size, marbling state of the lean tissue, color of the fat and lean tissue, and thickness of back fat of the 13th rib. To evaluate the beef quality, extracting loin parts from the sectional image of the 13th beef rib is crucial and is the first step. However, because of the inhomogeneous distribution and fuzzy pattern of the fat and lean tissues on the beef cut, it is difficult to extract automatically the proper contour of the lean tissue. In this paper, a prototype mobile beef quality measurement system, which can be implemented practically at the beef processing site was developed. The developed system was composed of the hand held image acquisition unit and mobile processing unit mounted with touch-pad screen. Algorithms to extract the boundary of the lean tissue and a proper tool to evaluate the marbling status have been developed using color image processing. The boundary extraction algorithm showed successful results for the beef cuts with simple and moderate patterns of the lean tissue and fat. However, it had some difficulty in eliminating complex pattern of the extraneous tissues adhered to the lean tissue in the boundary extraction. The developed algorithms were implemented to the prototype mobile processing unit.