• Title/Summary/Keyword: Fuzzy color

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Color Seal Extraction of Document Images using An Extended Fuzzy Integral (확장된 퍼지적분을 이용한 문서영상의 컬러낙관 추출)

  • Park, In-Kyu;Choi, Gyoo-Seok
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.9 no.1
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    • pp.31-37
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    • 2009
  • This paper casts an application of an extended fuzzy integral on the selective extraction of color clusters characterized by a particular color hue from color document images. Despite of the negative role of fuzzy integral, the presented approach attains the detection of the seals through the neighborhood information via the center of area method. The conventional fuzzy integral evaluates the negative aspects of the importance about the items by min operator, which result in the discontinuous parts of seals. In an attempt to cope with the drawback our approach considers the integral aspects via the center of area method, which results in the robustness of the images. Finally, the framework is successfully tested on a data set formed by documents from a real application for the detection.

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Metal Object Detection System For Drive Inside Protection (내부 운전자 보호를 위한 금속 물체 탐지 시스템)

  • Kim, Jin-Kyu;Joo, Young-Hoon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.19 no.5
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    • pp.609-614
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    • 2009
  • The purpose of this paper is to design the metal object detection system for drive inside protection. To do this, we propose the algorithm for designing the color filter that can detect the metal object using fuzzy theory and the algorithm for detecting area of the driver's face using fuzzy skin color filter. Also, by using the proposed algorithm, we propose the algorithm for detecting the metallic object candidate regions. And, the metallic object color filter is then applied to find the candidate regions. Finally, we show the effectiveness and feasibility of the proposed method through some experiments.

Color Detection and Psychology Analysis Using Fuzzy Reasoning Method (퍼지 추론 기법을 이용한 색상 추출과 심리 분석)

  • Cho, Jae-Hyun
    • The Journal of the Korea institute of electronic communication sciences
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    • v.10 no.3
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    • pp.381-386
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    • 2015
  • In recent, many researches have been studying sensitivity and psychology of human being on color and the necessity of psychology therapy by color. Among them, a picture of children can be a tool to represent their emotion. Information of colors and direction on a child's picture often represent his internal psychological states unconsciously and is different from the brightness of a color. In this paper, we propose a method to extract domain colors by color classification and subdivision the classes of brightness using fuzzy inference. In addition, it is shown that our method is used for analysing the psychology status of children through their pictures.

The development of intelligent agent system on color planning using fuzzy theory (퍼지이론을 이용한 색채계획 지능형 에이전트 시스템 개발)

  • Lee, Joon-Whoan;Eum, Kyoung-Bae;Hyoung, A-Young
    • Science of Emotion and Sensibility
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    • v.11 no.1
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    • pp.1-10
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    • 2008
  • We developed the decision support system by using the fuzzy theory. This system designs harmonious color space according to the linguistic input. This input represents the atmosphere which the user want. If the linguistic input of adjective image scale is given in the developed system, the relation between the adjective and color is supposed as fuzzy relation. The color which match with the whole atmosphere of color space is selected. The search region of harmonious color decision is controlled by the knowledge on color harmony of Moon-Spencer. Harmonious color is selected by it.

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The emotional evaluation of color pattern based on information fusion (정보융합 기법을 이용한 칼라 패턴의 감성 평가)

  • 김성환;엄경배;이준환
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2000.11a
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    • pp.23-27
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    • 2000
  • In this paper, we propose an emotional evaluation model based on information fusion. This model can transform the physical features of a color pattern to the emotional features. Our proposed model consists of the fuzzy logic system and neural network model. The evaluation values produced by them were fused. The model shows comparable performances to the neural network and fuzzy logic system for the approximation of the nonlinear transforms. We believe the evaluated results of a color pattern can be used to the emotion-based color image retrievals.

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CMAC Neuro-Fuzzy Design for Color Calibration (컬러재현을 위한 CMAC의 뉴로퍼지 설계)

  • 이철희;변오성;문성룡;임기영
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2001.05a
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    • pp.97-100
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    • 2001
  • CMAC model was proposed by Albus [6] to formulate the processing characteristics of the human cerebellum. Instead of the global weight updating scheme used in the back propagation, CMAC use the local weight updating scheme. Therefore, CMAC have the advantage of fast learning and high convergence rate. In this paper, simulate Color Calibration by CMAC in color images and design hardware by VHDL-base high-level synthesis.

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Developments of Parking Control System Using Color Information and Fuzzy C-menas Algorithm (컬러 정보와 퍼지 C-means 알고리즘을 이용한 주차관리시스템 개발)

  • 김광백;윤홍원;노영욱
    • Journal of Intelligence and Information Systems
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    • v.8 no.1
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    • pp.87-101
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    • 2002
  • In this paper, we proposes the car plate recognition and describe the parking control system using the proposed car plate recognition algorithm. The car plate recognition system using color information and fuzzy c-means algorithm consists of the extraction part of a car plate from a car image and the recognition part of characters in the extracted car plate. This paper eliminates green noise from car image using the mode smoothing and extract plate region using green and white information of RGB color. The codes of extracted plate region is extracted by histogram based approach method and is recognized by fuzzy c-means algorithm. For experimental, we tested 80 car images. We shows that the proposed extraction method is better than that from the color information of RGB and HSI, respectively. So, we can know that the proposed car plate recognition method using fuzzy c-means algorithm was very efficient. We develop the parking control system using the proposed car plate recognition method, which showed performance improvement by the experimental results.

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Feature Extraction for Protein Pattern Using Fuzzy Integral (퍼지적분을 이용한 단백질패턴에 관한 특징추출)

  • Song, Young-Jun;Kwon, Heak-Bong;Kim, Mi-Hye
    • The Journal of the Korea Contents Association
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    • v.7 no.1
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    • pp.40-47
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    • 2007
  • In the protein macro array image, it is important to find out the feature of the each protein chip. A decision error by the personal sense of sight occurred from long time observation while making an experiment in many protein chip image. So the feature extraction is needed by a simulator. In the case of feature analysis for macro array scan image the efficiency is maximized. In the fluorescence scan image, the response for each cell have been depend on R, G, B distribution of color image. But it is difficult to be classified as one color feature in the case of mixed color image. In this paper, the response color of a protein chip is classified according to the fuzzy integral value with respect to fuzzy measure as the user desired color. The result of the experiment for the macro array fluorescence image with the Scan Array 5000 shows that the proposed method using the fuzzy integral is important fact to be make decision for the ambiguous color.

Real Time Recognition of Finger-Language Using Color Information and Fuzzy Clustering Algorithm

  • Kim, Kwang-Baek;Song, Doo-Heon;Woo, Young-Woon
    • Journal of information and communication convergence engineering
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    • v.8 no.1
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    • pp.19-22
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    • 2010
  • A finger language helping hearing impaired people in communication A sign language helping hearing impaired people in communication is not popular to ordinary healthy people. In this paper, we propose a method for real-time sign language recognition from a vision system using color information and fuzzy clustering system. We use YCbCr color model and canny mask to decide the position of hands and the boundary lines. After extracting regions of two hands by applying 8-directional contour tracking algorithm and morphological information, the system uses FCM in classifying sign language signals. In experiment, the proposed method is proven to be sufficiently efficient.

Control of Convergence for Deflection Yoke Using Neuro-Fuzzy Model (뉴로 퍼지 모델을 이용한 편향요크의 RGB색 일치에 대한 제어)

  • 정병묵;임윤규;정창욱
    • Journal of the Korean Society for Precision Engineering
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    • v.15 no.5
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    • pp.19-27
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    • 1998
  • Color Display Tube (CDT) used in computer monitors, consists of many components. Deflection Yoke(DY) among them supplies the vertical and horizontal magnetic fields so that the spatial trajectories of electron beams are deflected according to the synchronization signals. If the magnetic fields are not correctly formed, there will be color blurring or blooming by a mis-convergence of each beam and the color image on screen may not be clear. Therefore, in the manufacture of DY. its quality is strictly examined to get the desired convergence and the occurred mis-convergence can be cured by sticking ferrite sheets on the inner part of DY. However, because it needs expert's knowledge and experience to find the proper position of the sheet, this article introduces an intelligent controller that the knowledge-base represented by a neuro-fuzzy model is used to find the optimal position of the ferrite sheet for the convergence.

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