• Title/Summary/Keyword: 화소 분포

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Detection of Defects on Repeated Multi-Patterned Images (반복되는 다수 패턴 영상에서의 불량 검출)

  • Lee, Jang-Hee;Yoo, Suk-In
    • Journal of KIISE:Software and Applications
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    • v.37 no.5
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    • pp.386-393
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    • 2010
  • A defect in an image is a set of pixels forming an irregular shape. Since a defect, in most cases, is not easy to be modeled mathematically, the defect detection problem still resides in a research area. If a given image, however, composed by certain patterns, a defect can be detected by the fact that a non-defect area should be explained by another patch in terms of a rotation, translation, and noise. In this paper, therefore, the defect detection method for a repeated multi-patterned image is proposed. The proposed defect detection method is composed of three steps. First step is the interest point detection step, second step is the selection step of a appropriate patch size, and the last step is the decision step. The proposed method is illustrated using SEM images of semiconductor wafer samples.

A Study on Efficient Coding Mode Decision for H.264/AVC (H.264/AVC의 효율적인 부호화 모드 결정에 관한 연구)

  • Hur, Tae-Won
    • Journal of the Korea Computer Industry Society
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    • v.6 no.5
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    • pp.801-812
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    • 2005
  • H.264/AVC is the international video coding standard which has significant improvements of coding efficiency. ITU-T(International Telecommunication Union-Telecommunication standardization sector) and MPEG(Moving Picture Experts Group) adopts various complex coding tool such as variable block size motion, multiple reference frames, quarter-pel motion estimation/compensation (ME/MC) and rate-distortion(RD) optimization, etc. H.264 reference model employs complex mode decision technique based on RD optimization which requires high computational complexity. In this paper, we propose an efficient coding mode decision based on the cost distribution of RD in the macroblock coding mode sequence. Simulation results show that the proposed method reduces encoding time by 34% on average and save the number of computing RD cost by 82%.

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Noise Reduction Method for Image Using Transition-Parameter of Cellular Automata (셀룰러 오토마타의 천이 파라미터를 이용한 영상의 잡음제거 방법)

  • Kim, Tai-Suk;Lee, Seok-Ki;Kwon, Soon-Kak;Kwon, Oh-Jun
    • Journal of Korea Multimedia Society
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    • v.13 no.9
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    • pp.1329-1336
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    • 2010
  • Cellular Automata is a discrete dynamical system which natural phenomena may be specified completely in terms of local relation, can increase and decrease the difference of luminance locally according to transition rule by keeping the characteristic of target image. In this paper, we propose a noise reduction method by keeping the characteristic using transition rule of Cellular Automata, also we propose methods of effective transition rule, the selection of parameters, the selection of number of neighborhood pixels. For uniform distribution noise, Gaussian noise, impulse noise, we do an experiment on adaptive state using different mathematical operations and compare its results. It was confirmed that the proposed transition rule is based on fast convergence speed and has stabile results.

Contour and Feature Parameter Extraction for Moving Object Tracking in Traffic Scenes (도로영상에서 움직이는 물체 추적을 위한 윤곽선 및 특징 파라미터 추출)

  • Lee, Chul-Hun;Seol Sung-Wook;Joo Jae-Heum;Nam Ki-Gon
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.37 no.1
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    • pp.11-20
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    • 2000
  • This paper presents the method of extracting the contour and shape parameters for moving object tracking in traffic scenes. The contour is extracted by applying difference image method in reduction image and the features are extracted from original image to grow the accuracy of tracking. We used features such as circle distribution, center moment, and maximum and minimum ratio. Data association problem is solved by these features. Kalman filters are used for moving object tracking on real time. The simulation results indicate that the proposed algorithm appears to generate feature vectors good enough for multiple vehicle tracking.

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Lane detection method using the Retinex algorithm in foggy roads (Retinex 알고리즘을 사용한 안개 구간에서의 차선 검출 방법)

  • Kang, ji-hun;Choi, seo-hyuk;Kim, chang-dae;Ryu, sung-pil;Kim, dong-woo;Ahn, jae-hyeong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2015.05a
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    • pp.376-380
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    • 2015
  • This paper proposes new recognition method of road lanes misty day. The method enables autonomous-driving of cars and the safety of the drivers while driving with bad visibility in foggy roads. The proposed method, firstly, determines whether the foggy or not according to pixel number distributions and starting point of the fog period from input images. If it is foggy then the median filter's size of the Retinex algorithm is set to 1000 or more and it performs histogram equalization and normalization. The computer simulation results show that the proposed method can recognize better long distances and fine detection than earlier methods.

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Adaptive Retinex Back-light Compensation Algorithm Using Skewness Information of Image (영상에서 비대칭도 정보를 이용한 적응적인 Retinex 역광 보정 알고리즘)

  • Jeong, Jae-Hyun;Kang, Duk-Goo;Hong, Min-Cheol
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.36 no.8C
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    • pp.497-504
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    • 2011
  • This paper presents an adaptive retinex algorithm, In order to solve typical problems of retinex algorithm such as expensive computational cost, halo artifact, and color distortion, a function of skewness that represents a statistical distribution of pixels is defined to compensate contrast and color distortion. The experimental results show that the proposed algorithm leads to subjectively better performance than typical retinex algorithm, and that the proposed algorithm has the capability to reduce approximately 40% computational cost than typical retinex algorithm.

SPOT Camera Modeling Using Ephemeris Data (궤도자료를 이용한 SPOT 카메라 모델링)

  • 김만조;차승훈;고보연
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2003.04a
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    • pp.531-536
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    • 2003
  • In this paper, a camera modeling method that utilizes ephemeris data and imaging geometry is presented. The proposed method constructs a mathematical model only with parameters that are contained in the leader file and does not require any ground control points for model construction. Control points are only needed to eliminate geolocation error of the model that is originated from errors in the parameters that are used in model construction. With few (one or two) of control points, RMS error of less than pixel size can be obtained and control points are not necessarily uniformly distributed over the entire scene. This advantage is crucial in large project and will enable to reduce project cost dramatically.

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An Efficient BLU Inspection Using Noise-Tolerant Context-free Attention Operator (잡음에 강건한 주목 연산자를 이용한 효과적인 BLU 얼룩 검사)

  • Park, Chang-Jun;Choe, Heung-Mun
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.38 no.6
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    • pp.640-647
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    • 2001
  • In this paper, a noise-tolerant generalized symmetry transform(NTGST) is proposed as an effective attention operator for the spot detection in BLU inspection, in which various spots with variable sizes, shapes, gray levels, and low contrast, should be detected from the complex, noisy background with lattice shaped shading. The proposed NTGST takes into account the polarity of convergence and divergence of the radial orientation of the intensity gradient as well as it's magnitude and symmetry, and thereby can detect only the BLU spots from the noisy and lattice shaped shadows of background. Experiments are conducted on the BLU inspection image obtained by CCD camera, and the proposed NTGST is Proved to be effectively used in BLU inspection.

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Nucleus Recognition of Uterine Cervical Pap-Smears using Kapur Method and Fuzzy Reasoning Rule (Kapur 방법과 퍼지 추론 규칙을 이용한 자궁 경부진 핵 인식)

  • Kang, Kyoung-Min;Kim, Kwang-Baek
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2007.06a
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    • pp.241-247
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    • 2007
  • 자궁 경부 세포진 영상의 핵 추출을 위해서는 영상의 배경과 핵 그리고 세포질 영역의 구분이 중요하다. 또한 정상 세포핵과 암종 세포핵의 구분 및 인식을 위해서는 세포핵들의 형태학적 특징을 이용한 분류 기준을 세워야한다. 본 논문에서는 자궁 경부 세포진 영상에서 세포핵의 후보 영역과 핵을 추출하기 위해 현미경 400배율 확대 사진을 획득하는 과정에서 훼손된 컬러 영상을 복원하기 위한 방법으로 Lighting Compensation을 적용하여 영상을 보정한다. 그리고 배경 영역과 세포핵 영역을 구분하기 위해 영상의 R,G,B 영역의 히스토그램의 분포를 이용하여 배경을 제거한다. 배경이 제거된 영상을 그레이 영상으로 변환 한 후, 히스토그램 명암도의 값을 이용하여 세포핵 영역과 세포질을 분류하여 세포핵 영역을 추출한다. 그리고 Kapur 방법을 적용하여 세포핵 영역의 엔트로피 누적확률을 구한 후, 영상을 이진화 한다. Kapur 방법이 적용된 이진화 영상에서 세포핵 영역의 중심과 주위 화소를 비교하는 $3\times3$ 마스크를 적용하여 영상의 미세한 잡음을 제거 한 후, 8방향 윤곽선 추적 알고리즘을 적용하여 최종적으로 세포핵 영역을 추출한다. 추출된 세포핵의 영역을 분류 및 인식하는 과정으로 세포의 외각의 방향성 정보, 핵의 크기, 그리고 면적 비율의 특징을 이용하여 퍼지 소속 함수를 설계한 후, 소속 함수의 소속도를 구하고 퍼지 추론 규칙을 적용하여 자궁 경부 세포진 영상에서 정상 세포핵 및 암종 세포핵을 인식한다.

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A Study on Edge Detection Algorithm using Grey Level Converting Function (그레이 레벨 변환 함수를 이용한 에지 검출 알고리즘에 관한 연구)

  • Lee, Chang-Young;Hwang, Yeong-Yeun;Kim, Nam-Ho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2015.10a
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    • pp.921-923
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    • 2015
  • Edge in the image includes the size, direction and location of objects. The existing detection methods for detecting this edge is a method using Sobel, Prewitt, Roberts and Laplacian, etc. These existing methods use a fixed weighted mask in order to detect the edge and have somewhat insufficient edge detection characteristics. Therefore in this paper, an algorithm that detects the edge by applying the grey level converting function according to the pixel distribution of local mask was proposed.

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