• Title/Summary/Keyword: Image Region

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Emphysema Region Pre-Detection Method for Emphysema Disease Diagnosis using Lung CT Images (흉부 CT 영상에서 폐기종질환진단을 위한 폐기종영역 사전 탐지 기법)

  • Saipullah, Khairul Muzzammil;Peng, Shao-Hu;Park, Min-Wook;Kim, Deok-Hwan
    • Proceedings of the Korean Information Science Society Conference
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    • 2010.06c
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    • pp.447-451
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    • 2010
  • In this paper, we propose a simple but effective algorithm to increase the speed of Emphysema region classification. Emphysema region classification method based on CT image consumes a lot of time because of the large number of subregions due to the large size of CT image. Some of the sub-regions contain no Emphysema and the classification of these regions is worthless. To speed up the classification process, we create an algorithm to select Emphysema region candidates and only use these candidates in the Emphysema region classification instead of all of the sub-regions. First, the lung region is detected. Then we threshold the lung region and only select the dark pixels because Emphysema only appeared in the dark area of the CT image. Then the thresholded pixels are clustered into a region that called the Emphysema pre-detected region or Emphysema region candidate. This region is then divided into sub-region for the Emphysema region classification. The experimental result shows that Emphysema region classification using predetected Emphysema region decreases the size of lung region which will result in about 84.51% of time reduction in Emphysema region classification.

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Using Analysis of Major Color Component facial region detection algorithm for real-time image (동영상에서 얼굴의 주색상 밝기 분포를 이용한 실시간 얼굴영역 검출기법)

  • Choi, Mi-Young;Kim, Gye-Young;Choi, Hyung-Il
    • Journal of Digital Contents Society
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    • v.8 no.3
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    • pp.329-339
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    • 2007
  • In this paper we present a facial region detection algorithm for real-time image with complex background and various illumination using spatial and temporal methods. For Detecting Human region It used summation of Edge-Difference Image between continuous image sequences. Then, Detected facial candidate region is vertically divided two objected. Non facial region is reduced using Analysis of Major Color Component. Non facial region has not available Major Color Component. And then, Background is reduced using boundary information. Finally, The Facial region is detected through horizontal, vertical projection of Images. The experiments show that the proposed algorithm can detect robustly facial region with complex background various illumination images.

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Image segmentation based on hierarchical structure and region merging using contrast for very low bit rate coding (초저속 부호화를 위한 계층적 구조와 대조를 이용한 영역 병합에 의한 영상 분할)

  • 송근원;김기석;박영식;이호영;하영호
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.34S no.11
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    • pp.102-113
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    • 1997
  • In this paepr, a new image segmentation method reducing efficiently contour information causing bottleneck problem at segmentatio-based very low bit rate codingis proposed, while preserving objective and subjective quality. It consists of 4-level hierarchical image segmentation based on mathematical morphology and 1-leve region merging structure using contast of two adjacent regions. For two adjacent region pairs at the fourth level included in each region of the thid level, contrast is calculated. Among the pairs of two adjacent regions with less value than threshold, two adjacent regions having the minimum contrast are merged first. After region merging, texture of the merged region is updated. The procedure is performed recursively for all the adjacent region pairs at the fourth level included in each region of the third level. Compared with the previous method, the objective and subjective image qualities are similar. But it reduces 46.65% texture information on the average by decreasing total region number to be tansmitted. Specially, it shows reduction of the 23.95% contour information of the average. Thus, it can improve efficiently the bottleneck problem at segementation-based very low bit rate coding.

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Character Region Extraction of Monumental Inscription Image Using Boundary Information (윤곽선 정보를 이용한 금석문 영상의 글자 영역 추출)

  • 최호형;박영식;김기석
    • Proceedings of the Korea Multimedia Society Conference
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    • 2002.11b
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    • pp.118-121
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    • 2002
  • The study on shilla monumental inscription has been accomplished by many historians. However, the research on segmentation of monumental inscription image using digital image processing is not sufficient for restoration of the image. Although, many image processing methods have been proposed for region extraction in still image, there is no suitable method for accurate interpretation of monumental inscription image. To distinguish foreground and background region in the image, this paper presents new segmentation algorithm composed of contrast adjustment and median filtering, thresholding and sobel operation, as pre-processing and post-processing. The result show that background and foreground regions are segmented in monumental inscription image.

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A Study On Watershed Region Extraction Based On Edge Information (에지 정보를 이용한 watershed 영역 추출에 관한 연구)

  • 이원효;조상현;설경호;주동현;김두영
    • Proceedings of the IEEK Conference
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    • 2003.11a
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    • pp.449-452
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    • 2003
  • This paper propose a extracting method of the region for image using segmentation and edge information. First propose algorithm extract information using canny edge detector and the image was divided by watershed segmentation. And it extract the mage with edge information by merging region. Finally we compare the proposed method with levelset method. In the result proposed method not only extract the image with accurate region but also reduce operation time.

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Color Image Segmentation Using Anisotropic Diffusion and Agglomerative Hierarchical Clustering (비등방형 확산과 계층적 클러스터링을 이용한 칼라 영상분할)

  • 김대희;안충현;호요성
    • Proceedings of the IEEK Conference
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    • 2003.11a
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    • pp.377-380
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    • 2003
  • A new color image segmentation scheme is presented in this paper. The proposed algorithm consists of image simplification, region labeling and color clustering. The vector-valued diffusion process is performed in the perceptually uniform LUV color space. We present a discrete 3-D diffusion model for easy implementation. The statistical characteristics of each labeled region are employed to estimate the number of total clusters and agglomerative hierarchical clustering is performed with the estimated number of clusters. Since the proposed clustering algorithm counts each region as a unit, it does not generate oversegmentation along region boundaries.

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Image Data Compression Based On Region Analysis (Region 재구성에 의한 영상 Data압축)

  • Kim, Hae-Soo;Lee, Keun-Young
    • Proceedings of the KIEE Conference
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    • 1987.07b
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    • pp.1390-1393
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    • 1987
  • This paper describes the image data compression based on the image decomposition. We reduced the processing time using the segmentation based on the distribution of grey level, and obtained high compression rate using the Huffman run-length coding for the segmented image, and the 2-Dimensional least square curve fitting and the shift coder for each region.

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Facial Region Extraction in an Infrared Image (적외선 영상에서의 얼굴 영역 자동 추적)

  • Shin, S.W.;Kim, K.S.;Yoon, T.H.;Han, M.H.;Kim, I.Y.
    • Proceedings of the KIEE Conference
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    • 2005.05a
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    • pp.57-59
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    • 2005
  • In our study, the automatic tracking algorithm of a human face is proposed by utilizing the thermal properties and 2nd momented geometrical feature of an infrared image. First, the facial candidates are estimated by restricting the certain range of thermal values, and the spurious blobs cleaning algorithm is applied to track the refined facial region in an infrared image.

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A Study on Image Pixel Classification Using Directional Scales (방향성 정보 척도를 이용한 영상의 픽셀분류 방법에 관한 연구)

  • 박중순;김수겸
    • Journal of Advanced Marine Engineering and Technology
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    • v.28 no.4
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    • pp.587-592
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    • 2004
  • Pixel classification is one of basic issues of image processing. The general characteristics of the pixels belonging to various classes are discussed and the radical principles of pixel classification are given. At the same time, a pixel classification scheme based on image information scales is proposed. The proposed method is overcome that computation amount become greater and contents easily get turned. And image directional scales has excellent anti-noise performance. In the result of experiment. good efficiency is showed compare with other methods.

Sequential Defect Region Segmentation according to Defect Possibility in TFT-LCD Image (TFT-LCD영상에서 결함 가능성에 따른 순차적 결함영역 분할)

  • Chang, Chung Hwan;Lee, SeungMin;Park, Kil-Houm
    • Journal of Korea Multimedia Society
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    • v.23 no.5
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    • pp.633-640
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    • 2020
  • Defect region segmentation of TFT-LCD images is performed by combining defect pixels detected by a defect detection method into defect region, or by using morphological operations to segment defect region. Therefore, the result of segmentation of the defect region is highly dependent on the defect detection result. In this paper, we propose a method which segments defect regions sequentially according to the possibility of being included in defect regions in TFT-LCD images. The proposed method repeats the process of detecting a seed using the median value and the median absolute deviation of the image, and segments the defect region using the seeded region growing method. We confirmed the superiority of the proposed method to segment defect regions using pseudo-images and real TFT-LCD images.