• Title/Summary/Keyword: gray level

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Selection Method of Multiple Threshold Based on Probability Distribution function Using Fuzzy Clustering (퍼지 클러스터링을 이용한 확률분포함수 기반의 다중문턱값 선정법)

  • Kim, Gyung-Bum;Chung, Sung-Chong
    • Journal of the Korean Society for Precision Engineering
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    • v.16 no.5 s.98
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    • pp.48-57
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    • 1999
  • Applications of thresholding technique are based on the assumption that object and background pixels in a digital image can be distinguished by their gray level values. For the segmentation of more complex images, it is necessary to resort to multiple threshold selection techniques. This paper describes a new method for multiple threshold selection of gray level images which are not clearly distinguishable from the background. The proposed method consists of three main stages. In the first stage, a probability distribution function for a gray level histogram of an image is derived. Cluster points are defined according to the probability distribution function. In the second stage, fuzzy partition matrix of the probability distribution function is generated through the fuzzy clustering process. Finally, elements of the fuzzy partition matrix are classified as clusters according to gray level values by using max-membership method. Boundary values of classified clusters are selected as multiple threshold. In order to verify the performance of the developed algorithm, automatic inspection process of ball grid array is presented.

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New Gray Level Corner Point Detection Method (새로운 그레이 레벨 코너점 검출 방법)

  • 나재형;오해석
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.8C
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    • pp.1062-1068
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    • 2004
  • In this paper, we introduce a new gray level comer detection method to recognize corner points accurately. The new corner detector divides the corner region into many homocentric circles according to the window size, and calculates the corner response and angle of corner area about each layer to get an accurate corner point. The new corner detector has a hierarchical structure so it can detect corner point more quickly than general gray level corner detector

Development for Automatic Thickness Measurment System by Digital Image Processing (디지탈 이미지 프로세싱을 이용한 자동두께 측정장치 개발)

  • 김영일;이상길
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1993.10a
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    • pp.395-401
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    • 1993
  • The purpose of this paper is to develop an automatic measuring system based on the digital image processing which can be applied to the in-process measurement of the characteristics of the thin thickness. The derivative operators is used for edge detection in gray level image. This concept can be easiliy illustrated with the aid of object shows an image of a simple light object on a dark background, the gray level profile along a horizontal scan line of the image, and the first and second derivatives of the profile. The first derivative of an edge modeled in this manner is () in all regions of constant gray level, and assumes a constant value during a gray level transition. The experimental results indicate that the developed qutomatic inspection system can be applied in real situation.

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A Classifier for Textured Images Based on Matrix Feature (행렬 속성을 이용하는 질감 영상 분별기)

  • 김준철;이준환
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.31B no.3
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    • pp.91-102
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    • 1994
  • For the analysis of textured image, it requires large storage space and computation time to calculate the matrix features such as SGLDM(Spatial Gray Level Dependence Matrix). NGLDM(Neighboring Gray Level Dependence Matrix). NSGLDM(Neighboring Spatial Gray Level Dependence Matrix) and GLRLM(Gray Level Run Length Matrix). In spite of a large amount of information that each matrix contains, a set of several correlated scalar features calculated from the matrix is not sufficient to approximate it. In this paper, we propose a new classifier for textured images based on these matrices in which the projected vectors of each matrix on the meaningful directions are used as features. In the proposed method, an unknown image is classified to the class of a known image that gives the maximum similarity between the projected model vector from the known image and the vector from the unknown image. In the experiment to classify images of agricultural products, the proposed method shows good performance as much as 85-95% of correct classification ratio.

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Luminance Control for a Given Gray Level by the Asymmetric Sustain Pulse Amplitude in AC PDP (주어진 계조 하에서 불평형 서스테인 펄스를 이용한 AC PDP의 휘도제어)

  • Lee Sun-Hong;Park Chung-Hoo;Choi Joon-Young
    • The Transactions of the Korean Institute of Electrical Engineers C
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    • v.54 no.4
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    • pp.161-165
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    • 2005
  • Need of a dimmer function becomes more important with increasing interest on a HDTV for home theater applications. In a conventional AC PDP, a possible method to reduce luminance of a whole Panel is to reduce a total number of sustain pulses and then to change the gray level. However, the reduction of the total sustain number causes the step of luminance to be rough. Moreover, it is impossible to control the luminance of the panel for a given gray level. In this paper, a simple and robust method is proposed to control linearly the luminance of whole panel by applying the asymmetric sustain pulses in the display period of the ADS driving scheme. As the range of luminance control by the proposed method is about $50\%$ for a given gray level. Moreover, it is experimentally verified that the proposed method shows similar dynamic margin performances compare with the conventional method.

Development for Automatic Thickness Measurment System by Digital Image Processing (디지탈 영상처리 기법을 이용한 자동 두께측정 장치 개발)

  • Kim, Y.I.
    • Journal of the Korean Society for Precision Engineering
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    • v.12 no.6
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    • pp.72-79
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    • 1995
  • The purpose of this paper is to develop an automatic measuring system based on the digital image processing which can be applied to the in-process measurment of the characteristics of the thin thickness. The derivative operators is used for edge detection in gray level image. This concept can be easily illustrated with the aid of object shows an image of a simple light object on a dark background, the gray level profile along a horizontal scan line of the image, and the first and second derivatives of the profile. The first derivative of an edge modeled in this manner is 0 in all regions of constant gray level, and assumes a constant value during a gray level transition. The experimental results indicate that the developed automatic inspection system can be applied in real situation.

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Reduction of Variable Illumination Effect on Pixel Gray-levels of Machine Vision

  • Suh S. R.;Huang J. K.;Kim Y. T.;Yoo S. N.;Choi Y. S.;Sung J. H.
    • Agricultural and Biosystems Engineering
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    • v.5 no.1
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    • pp.5-9
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    • 2004
  • This study was carried out to develop methods of reducing the effect of solar illumination on pixel gray-levels of machine vision for agricultural field use. Two kinds of monochrome CCD cameras with manual and auto-iris lenses were used to take pictures within a range of 15 to 120 klux of solar illumination. A camera having more precise automatic control functions gave much better result. Four kinds of indices using pixel gray-level of the $99\%$ white DRS (diffuse reflectance standard) as a reference were tried to compensate pixel gray-levels of an image for variable illumination. Coefficients of variation of the indices within a range of illumination were used as a criterion for comparison. The study concluded that an index of (A+B)/A, where A is gray-level of the $99\%$ DRS and B is gray-level of the tested material, gave the best consistency in the range of solar illumination.

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The Segmentation of white matter and gray matter from brain MR Image (뇌의 자기공명(MR) 영상에서 백질과 회백질의 추출)

  • 유현경;박종원;송창준
    • Proceedings of the Korean Information Science Society Conference
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    • 1999.10b
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    • pp.431-433
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    • 1999
  • 본 논문에서는 뇌의 자기공명(이하 MR로 줄임) 영상에서 양측 대뇌반구의 뇌백질과 뇌회백질의 추출에 관하여 연구하였다. MR 영상은 특정 장기에서 일정한 gray level 값을 유지하는 전산화단층촬영(이하 CT로 줄임) 영상과는 달리 사람마다 gray level 값이 다르며 한 사람에 대해서도 각 슬라이스에 따라 gray level 값이 다르므로 각 슬라이스별로 조직의 특성을 파악하여 백질과 회백질의 추출에 이용하였다. 먼저 뇌를 둘러싸고 있는 두피, 근육, 두개골과 함께 안구를 제거한 후 두 개강 내에 위치한 뇌간과 소뇌의 특성을 차례로 인식하여 대뇌반구로부터 분리한 후 제거하였다. 또한 추출된 대뇌의 영상으로부터 백질과 회백질의 체적을 구하고, 뇌신경게 진단방사선과 전문의의 manual 작업과 비교하여 본 논문에서 제시한 방법의 정확도를 검증하였다.

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Block Classification of Document Images Using the Spatial Gray Level Dependence Matrix (SGLDM을 이용한 문서영상의 블록 분류)

  • Kim Joong-Soo
    • Journal of Korea Multimedia Society
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    • v.8 no.10
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    • pp.1347-1359
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    • 2005
  • We propose an efficient block classification of the document images using the second-order statistical texture features computed from spatial gray level dependence matrix (SGLDM). We studied on the techniques that will improve the block speed of the segmentation and feature extraction speed and the accuracy of the detailed classification. In order to speedup the block segmentation, we binarize the gray level image and then segmented by applying smoothing method instead of using texture features of gray level images. We extracted seven texture features from the SGLDM of the gray image blocks and we applied these normalized features to the BP (backpropagation) neural network, and classified the segmented blocks into the six detailed block categories of small font, medium font, large font, graphic, table, and photo blocks. Unlike the conventional texture classification of the gray level image in aerial terrain photos, we improve the classification speed by a single application of the texture discrimination mask, the size of which Is the same as that of each block already segmented in obtaining the SGLDM.

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A New Automatic Thresholding of Gray-Level Images Based on Maximum Entropy of Two-Dimensional Pixel Histogram (이웃 화소간 이차원 히스토그램 엔트로피 최대화를 이용한 명도영상 임계값 설정)

  • 김호연;남윤석;김혜규;박치항
    • Proceedings of the IEEK Conference
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    • 2000.11d
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    • pp.77-80
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    • 2000
  • In this paper, we present a new automatic thresholding algorithm based on maximum entropy of two-dimensional pixel histogram. While most of the previous algorithms select thresholds depending only on the histogram of gray level itself in the image, the presented algorithm considers 2D relational histogram of gray levels of two adjacent pixels in the image. Thus, the new algorithm tends to leave salient edge features on the image after thresholding. The experimental results show the good performance of the presented algorithm.

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