• Title/Summary/Keyword: 컬러 모형

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Color Image Segmentation Based on Morphological Operation and a Gaussian Mixture Model (모폴로지 연산과 가우시안 혼합 모형에 기반한 컬러 영상 분할)

  • Lee Myung-Eun;Park Soon-Young;Cho Wan-Hyun
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.43 no.3 s.309
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    • pp.84-91
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    • 2006
  • In this paper, we present a new segmentation algorithm for color images based on mathematical morphology and a Gaussian mixture model(GMM). We use the morphological operations to determine the number of components in a mixture model and to detect their modes of each mixture component. Next, we have adopted the GMM to represent the probability distribution of color feature vectors and used the deterministic annealing expectation maximization (DAEM) algorithm to estimate the parameters of the GMM that represents the multi-colored objects statistically. Finally, we segment the color image by using posterior probability of each pixel computed from the GMM. The experimental results show that the morphological operation is efficient to determine a number of components and initial modes of each component in the mixture model. And also it shows that the proposed DAEM provides a global optimal solution for the parameter estimation in the mixture model and the natural color images are segmented efficiently by using the GMM with parameters estimated by morphological operations and the DAEM algorithm.

Image Matching Method of Digital Surface Model Generation for Built-up Area (건물지역 수치표면모형 자동생성을 위한 영상정합 방법)

  • 박희주
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.18 no.3
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    • pp.315-322
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    • 2000
  • DSM(Digital Surface Model) is a digital model which represents the surface elevation of a region. DSM is necessary for orthoimage generation, and frequently used in man-made object extraction from aerial photographs nowadays. Image matching technique enables automatic DSM generation. This proposed a image matching method which can be applied to automatic generation of DSM for Built-up Area. The matching method proposed is to find conjugate points and conjugate lines from overlapping aerial images. In detecting conjugate points, the positional relation between possible conjugate point pair as well as correlation of pixel gray value is compared. In detecting conjugate lines, the color attribute of flank region of line, shape of line, positional relation between neighborhood points and lines, and the connection relation between lines are compared. The proposed matching method is assumed to be useful for DSM generation including Built-up Area.

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Vision-based Real-time Lane Detection and Tracking for Mobile Robots in a Constrained Track Environment

  • Kim, Young-Ju
    • Journal of the Korea Society of Computer and Information
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    • v.24 no.11
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    • pp.29-39
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    • 2019
  • As mobile robot applications increase in real life, the need of low cost autonomous driving are gradually increasing. We propose a novel vision-based real-time lane detection and tracking system that supports autonomous driving of mobile robots in constrained tracks which are designed considering indoor driving conditions of mobile robots. Considering the processing of lanes with various shapes and the pre-adjustment of operation parameters, the system structure with multi-operation modes are designed. In parameter tuning mode, thresholds of the color filter is dynamically adjusted based on the geometric property of the lane thickness. And in the unstable input mode of curved tracks and the stable input mode of straight tracks, lane feature pixels are adaptively extracted based on the geometric and temporal characteristics of the lanes and the lane model is fitted using the least-squared method. The track centerline is calculated using lane models and the motion model is simplified and tracked by a linear Kalman filter. In the driving experiments, it was confirmed that even in low-performance robot configurations, real-time processing produces the accurate autonomous driving in the constrained track.

Enhanced Binarization Method using Fuzzy Membership Function (퍼지 소속 함수를 이용한 개선된 이진화 방법)

  • 박경태;홍창수;김정원;전봉기;김광백
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2004.05b
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    • pp.162-165
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    • 2004
  • 대부분의 이진화 알고리즘은 임계치를 결정하기 위하여 히스토그램을 사용하여 밝기 분포를 분석한다. 배경과 물체의 명도차이가 큰 경우에는 분할을 위해 양봉 히스토그램을 보일 때는 최적의 임계치를 한기 위해 히스토그램 골짜기를 선택하는 것만으로도 양호한 임계치 결과를 얻을 수 있으나, 배경과 물체의 밝기 차이가 크지 않거나 자기 분포가 양봉 특성을 보이지 않을 때는 히스토그램 분석만으로 적절한 임계치를 얻기 어렵다. 본 논문에서는 RGB 컬러 모형의 각 색상에 대하여 퍼지 소속 함수를 적용하고, 그 결과를 이용해 배경에 비해 가독성이 높은 특징들을 배경과 분리하는 방법을 제시한다. 제안된 이진화 방법은 RGB의 각 색상에 퍼지 소속 함수를 적용하여 얻은 값들을 이용해 이진화한다. 기존의 임계치를 이용한 이진화 방법에 비해 잡음 영역을 상당히 제거 할 수 있으며, 컨테이너 영상에 적용한 결과, 기존의 방법에 비해 효율적인 것을 확인하였다.

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Pace and Facial Element Extraction in CCD-Camera Images by using Snake Algorithm (스네이크 알고리즘에 의한 CCD 카메라 영상에서의 얼굴 및 얼굴 요소 추출)

  • 판데홍;김영원;김정연;전병환
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2002.11a
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    • pp.535-542
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    • 2002
  • 최근 IT 산업이 급성장하면서 화상 회의, 게임, 채팅 등에서의 아바타(avatar) 제어를 위한 자연스러운 인터페이스 기술이 요구되고 있다. 본 논문에서는 동적 윤곽선 모델(active contour models; snakes)을 이용하여 복잡한 배경이 있는 컬러 CCD 카메라 영상에서 얼굴과 눈, 입, 눈썹, 코 등의 얼굴 요소에 대해 윤곽선을 추출하거나 위치를 파악하는 방법을 제안한다. 일반적으로 스네이크 알고리즘은 잡음에 민감하고 초기 모델을 어떻게 설정하는가에 따라 추출 성능이 크게 좌우되기 때문에 주로 단순한 배경의 영상에서 정면 얼굴의 추출에 사용되어왔다 본 연구에서는 이러한 단점을 파악하기 위해, 먼저 YIQ 색상 모델의 I 성분을 이용한 색상 정보와 차 영상 정보를 사용하여 얼굴의 최소 포함 사각형(minimum enclosing rectangle; MER)을 찾고, 이 얼굴 영역 내에서 기하학적인 위치 정보와 에지 정보를 이용하여 눈, 입, 눈썹, 코의 MER을 설정한다. 그런 다음, 각 요소의 MER 내에서 1차 미분과 2차 미분에 근거한 내부 에너지와 에지에 기반한 영상 에너지를 이용한 스네이크 알고리즘을 적용한다. 이때, 에지 영상에서 얼굴 주변의 복잡한 잡음을 제거하기 위하여 색상 정보 영상과 차 영상에 각각 모폴로지(morphology)의 팽창(dilation) 연산을 적용하고 이들의 AND 결합 영상에 팽창 연산을 다시 적용한 이진 영상을 필터로 사용한다. 총 7명으로부터 양 눈이 보이는 정면 유사 방향의 영상을 20장씩 취득하여 총 140장에 대해 실험한 결과, MER의 오차율은 얼굴, 눈, 입에 대해 각각 6.2%, 11.2%, 9.4%로 나타났다. 또한, 스네이크의 초기 제어점을 얼굴은 44개, 눈은 16개, 입은 24개로 지정하여 MER추출에 성공한 영상에 대해 스네이크 알고리즘을 수행한 결과, 추출된 영역의 오차율은 각각 2.2%, 2.6%, 2.5%로 나타났다.해서 Template-based reasoning 예를 보인다 본 방법론은 검색노력을 줄이고, 검색에 있어 Feasibility와 Admissibility를 보장한다.매김할 수 있는 중요한 계기가 될 것이다.재무/비재무적 지표를 고려한 인공신경망기법의 예측적중률이 높은 것으로 나타났다. 즉, 로지스틱회귀 분석의 재무적 지표모형은 훈련, 시험용이 84.45%, 85.10%인 반면, 재무/비재무적 지표모형은 84.45%, 85.08%로서 거의 동일한 예측적중률을 가졌으나 인공신경망기법 분석에서는 재무적 지표모형이 92.23%, 85.10%인 반면, 재무/비재무적 지표모형에서는 91.12%, 88.06%로서 향상된 예측적중률을 나타내었다.ting LMS according to increasing the step-size parameter $\mu$ in the experimentally computed. learning curve. Also we find that convergence speed of proposed algorithm is increased by (B+1) time proportional to B which B is the number of recycled data buffer without complexity of computation. Adaptive transversal filter with proposed data recycling buffer algorithm could efficiently reject ISI of channel and increase speed of convergence in avoidance burden of computational complexity in reality when it was experimented having the same condition of

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Image Quality Assessment Model of Natural Scene Based on Normal Distribution Analysis (일반 장면의 정규분포 분석을 기반으로 한 화질 측정 모형)

  • Park, Hyung-Ju;Har, Dong-Hwan
    • Science of Emotion and Sensibility
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    • v.16 no.3
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    • pp.373-386
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    • 2013
  • In this research, we specify the image consumers' preferred image quality ranges based on objective image quality evaluation factors and follow a method which measures preference of the natural image scenes. In other words, according to No-Reference, we select dynamic range, color, and contrast as factors of image quality measurements. For collecting sample images, we choose the preferred 200 landscapes which have over 30 recommendations by image consumers on the internet photo gallery. According to the scores of three objective factors of image quality measurements, the final expected score which means the image quality preference is measured and its total score is 100 points. In the main test, the actual image sample shows dynamic range 10 stop, LAB mean value L:54.7, A:2.96, B:-15.84, and RSC contrast 376.9. Total 200 image samples' normal distribution z value represents in dynamic range 0.21, LAB mean value L:0.15, A:0.38, B:0.13, and RSC contrast 0.08. In the standard normal distribution table, we can convert the z value as a percentage; dynamic range is 8.32%, LAB mean value is L:5.96%, A:14.8%, B:5.17%, and RSC contrast is 3.19%. And then, we convert the percentage values into the scores of 100; dynamic range is 91.68, LAB mean value is 91.36, and RSC contrast is 96.81. Therefore, we can conclude that the sample image's total mean score is 94.99 based on three objective image quality factors. Throughout our proposed image quality assessment model, we can measure the preference value of natural scenes. Also, we can specify the preferred image quality representation ranges and measure the expected image quality preference.

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A Method to Evaluate Rate of 'Soft-Hard' In a Drawing (그림의 '부드러운-딱딱한' 정도의 평가 방법)

  • Yoon, Seok-Hoon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.10 no.12
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    • pp.3963-3970
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    • 2009
  • This study proposes a method to evaluate the level of 'soft-hard' of color quantitatively by evaluating the shape with edge sharpness automatically and by evaluating color in the color image scale in a drawing in art therapy using a computer. The dependent variable is the rank for the color experts to rate the level of 'soft-hard'. The mean and standard deviation of Value(V), and Chroma(C), colors, main color, clusters, length of edge, and sharp line rate of edge are considered as the independent variable. The appropriate independent variables to explain the dependent variable are selected through the step wise regression analysis. The inter-rater reliability of two raters is checked and the validity of developed system is verified by the rank correlations coefficient between the ranks of rater's and system's. This system can be used to evaluate of the shape or color in a drawing objectively and quantitatively for art therapy assessment, and to give the useful information to the fashion, textile, interior industry as well as color psychology and art therapy.

Computerized Decision Support System for Real-time Flood Forecasting and Reservoir Control (홍수시(洪水時) 저수지(貯水池) 실시간(實時間) 운영(運營) 의사결정(意思決定) 지원(支援) 시스템)

  • Ko, Seok Ku;Lee, Han Goo;Lee, Hee Sung
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.12 no.1
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    • pp.131-140
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    • 1992
  • For a real-time flood forecasting and reservoir control problem of a multipurpose dam, the online acquisition of hydro-meteorological data and computerized analysis of the acquired data are absolutely necessary for the prompt decision of reservoir discharges which can minimize the possible damages and simultaneously maximize the utilization of the runoff. By introducing a man-machine interface such as condensed color graphics of the analyzed results, it is much easier and faster to transform the information to the decision maker who can decide the reservoir discharge. The newly developed PC-REFCON, which represents the PC based real-time flood forecasting and reservoir control, can easily handle the above problems by adopting a innovative decision support system. The system has three principal components of, a data base subsystem which acquires and manages real-time data, a model subsystem which forecasts the flood runoff and simulates the reservoir operation, and a dialogue subsystem which helps decision maker and system engineers using various graphics and tables with renovative methodologies. The developed PC-REFCON will be utilized from the coming Summer of 1992 for the flood control of all the nine multipurpose reservoirs in Korea.

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Enhanced Binarization Method using Fuzzy Membership Function (퍼지 소속 함수를 애용한 개선된 이진화 방법)

  • Kim Kwang Baek;Kim Young Ju
    • Journal of the Korea Society of Computer and Information
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    • v.10 no.1 s.33
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    • pp.67-72
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    • 2005
  • Most of image binarization algorithms analyzes the intensity distribution using the histogram for the determination of threshold value. When the intensity difference between the foreground object and the background is great, the histogram shows the tendency to be bimodal and the selection of the histogram valley as the threshold value shows the good result. On the other side. when the intensity difference is not great and the histogram doesn't show the bimodal property, the histogram analysis doesn't support the selection of the proper threshold value. This Paper Proposed the novel binarization method that applies the fuzzy membership function to each color value on the RGB color model and, by using the operation results, separates the features having the great readability from the background. The proposed method prevents the loss of information incurred by the gray scale conversion by using the RGB color model and extracts effectively the readable features by using the fuzzy inference Compared with the traditional binarization methods, the proposed method is able to remove the majority of noise areas and show the improved results on the image of transport containers , etc.

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A Study on Human Sensitivity Engineered Internal Landscape by Lighting Colors in Tunnels using LISREL Model (LISREL 모헝을 이용한 조명색채별 감성공학적 터널 내부경관 연구)

  • Park, Il-Dong;Ji, Kil-Ryong;Imm, Sung-bin;Kum, Ki-Jung
    • Journal of Korean Society of Transportation
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    • v.22 no.4 s.75
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    • pp.97-106
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    • 2004
  • It is a Known fact that driving through long tunnel increases possibility of traffic accident because of psychological feeling of insecurity and dispersion of drivers' concentration since driving in narrow and limited space for a longtime. It, therefore, results in raising transportation and environment problems, such as traffic accident difficult to be properly dealt with and ventilation. This study aims at proposing a method of augmenting driving amenity by improving the internal lighting facilities in the tunnel. The study is conducted by investigating internal landscapes of tunnels by lighting colors, which are currently being operated. The Color Planning System (CPS), developed by SHARP Co. Ltd, is exploited for selecting adjective that express the sensitivity image on lighting colors. The CPS is an example that applies to sensitivity of human body for products design development. The CPS takes the following process to define the color : 1) expressing "Pvoduct's Image" as "A Word (adjective)" and 2) referring "A Word" to "Image Scale", and 3) determining the color through this "Image Panel". The study is processed by making a questionnaire using the semantic differential (SD) scale, grasping the consciousness structure of experimental persons through the Factor Analysis, and building a model in which dependent variable is "Degree of Preference" about internal landscape in tunnel using LISREL(LInear Structural RELations).