• Title/Summary/Keyword: Region entropy

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Texture analysis of Thyroid Nodules in Ultrasound Image for Computer Aided Diagnostic system (컴퓨터 보조진단을 위한 초음파 영상에서 갑상선 결절의 텍스쳐 분석)

  • Park, Byung eun;Jang, Won Seuk;Yoo, Sun Kook
    • Journal of Korea Multimedia Society
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    • v.20 no.1
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    • pp.43-50
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    • 2017
  • According to living environment, the number of deaths due to thyroid diseases increased. In this paper, we proposed an algorithm for recognizing a thyroid detection using texture analysis based on shape, gray level co-occurrence matrix and gray level run length matrix. First of all, we segmented the region of interest (ROI) using active contour model algorithm. Then, we applied a total of 18 features (5 first order descriptors, 10 Gray level co-occurrence matrix features(GLCM), 2 Gray level run length matrix features and shape feature) to each thyroid region of interest. The extracted features are used as statistical analysis. Our results show that first order statistics (Skewness, Entropy, Energy, Smoothness), GLCM (Correlation, Contrast, Energy, Entropy, Difference variance, Difference Entropy, Homogeneity, Maximum Probability, Sum average, Sum entropy), GLRLM features and shape feature helped to distinguish thyroid benign and malignant. This algorithm will be helpful to diagnose of thyroid nodule on ultrasound images.

Region of Interest Heterogeneity Assessment for Image using Texture Analysis

  • Park, Yong Sung;Kang, Joo Hyun;Lim, Sang Moo;Woo, Sang-Keun
    • Journal of the Korea Society of Computer and Information
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    • v.21 no.11
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    • pp.17-21
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    • 2016
  • Heterogeneity assessment of tumor in oncology is important for diagnosis of cancer and therapy. The aim of this study was performed assess heterogeneity tumor region in PET image using texture analysis. For assessment of heterogeneity tumor in PET image, we inserted sphere phantom in torso phantom. Cu-64 labeled radioisotope was administrated by 156.84 MBq in torso phantom. PET/CT image was acquired by PET/CT scanner (Discovery 710, GE Healthcare, Milwaukee, WI). The texture analysis of PET images was calculated using occurrence probability of gray level co-occurrence matrix. Energy and entropy is one of results of texture analysis. We performed the texture analysis in tumor, liver, and background. Assessment textural features of region-of-interest (ROI) in torso phantom used in-house software. We calculated the textural features of torso phantom in PET image using texture analysis. Calculated entropy in tumor, liver, and background were 5.322, 7.639, and 7.818. The further study will perform assessment of heterogeneity using clinical tumor PET image.

Hyperbolic Reaction-Diffusion Equation for a Reversible Brusselator: Solution by a Spectral Method

  • 이일희;김광연;조웅인
    • Bulletin of the Korean Chemical Society
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    • v.20 no.1
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    • pp.35-41
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    • 1999
  • Stability characteristics of hyperbolic reaction-diffusion equations with a reversible Brusselator model are investigated as an extension of the previous work. Intensive stability analysis is performed for three important parameters, Nrd, β and Dx, where Nrd is the reaction-diffusion number which is a measure of hyperbolicity, β is a measure of reversibility of autocatalytic reaction and Dx is a diffusion coefficient of intermediate X. Especially, the dependence on Nrd of stability exhibits some interesting features, such as hyperbolicity in the small Nrd region and parabolicity in the large Nrd region. The hyperbolic reaction-diffusion equations are solved numerically by a spectral method which is modified and adjusted to hyperbolic partial differential equations. The numerical method gives good accuracy and efficiency even in a stiff region in the case of small Nrd, and it can be extended to a two-dimensional system. Four types of solution, spatially homogeneous, spatially oscillatory, spatio-temporally oscillatory and chaotic can be obtained. Entropy productions for reaction are also calculated to get some crucial information related to the bifurcation of the system. At the bifurcation point, entropy production changes discontinuously and it shows that different structures of the system have different modes in the dissipative process required to maintain the structure of the system. But it appears that magnitude of entropy production in each structure give no important information related for states of system itself.

Flash Flood Risk Assessment using PROMETHEE and Entropy Method (PROMETHEE와 Entropy 기법을 이용한 돌발홍수 위험도 평가)

  • Lee, Jung-Ho;Jun, Hwan-Don;Park, Moo-Jong;Jung, Jae-Hak
    • Journal of the Korean Society of Hazard Mitigation
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    • v.11 no.3
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    • pp.151-156
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    • 2011
  • Previously most of flood prevention efforts have been made for relatively large watersheds near to channel flow. However, as economical development and the expansion of leisure areas to mountainous region, human casualty by flash flood occurs frequently, requiring additional prevention activity. Therefore, to reduce the damage of human lives and property by flash flood, we develop an assessment method for flash flood occurrence for mountainous areas considering various factors involving it. PROMETHEE(Preference Ranking Organization METHod for Enrichment Evaluations) which is one of the MCDM(Multi-Criteria Decision Making) was adopted to assess the contribution of each factor to the risk of the flash flood in the mountainous area. The main evaluation criteria are classified into three categories, namely, the regional and rainfall characteristics, and geographical features. Also, the Entropy method is used to determine the weight of each evaluation criteria without survey. The suggested method based on PROMETHEE with Entropy method is applied to BongHwa region to verify its applicability. After applied, the method successfully assesses the relative risk of flash flood occurrence of each sub region in the BongHwa region. Out of the seventeen sub-regions, five, seven and five of them are evaluated as high-risk, medium-risk, and low-risk, respectively. To verify the results, we searched the historical data of flash flood and the flash flood had occurred in one of high-risk sub-regions at 2008.

Shape Extraction of Near Target Using Opening Operator with Adaptive Structure Element in Infrared hnages (적응적 구조요소를 이용한 열림 연산자에 의한 적외선 영상표적 추출)

  • Kwon, Hyuk-Ju;Bae, Tae-Wuk;Kim, Byoung-Ik;Lee, Sung-Hak;Kim, Young-Choon;Ahn, Sang-Ho;Sohng, Kyu-Ik
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.36 no.9C
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    • pp.546-554
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    • 2011
  • Near targets in the infrared (IR) images have the steady feature for inner region and the transient feature for the boundary region. Based on these features, this paper proposes a new method to extract the fine target shape of near targets in the IR images. First, we detect the boundary region of the candidate targets using the local variance weighted information entropy (WIE) of the original images. And then, a coarse target region can be estimated based on the labeling of the boundary region. For the coarse target region, we use the opening filter with an adaptive structure element to extract the fine target shape. The decision of the adaptive structure element size is optimized for the width information of target boundary by calculating the average WIE in the enlarged windows. The experimental results show that a proposed method has better extraction performance than the previous threshold algorithms.

Multi-level Thresholding using Fuzzy Clustering Algorithm in Local Entropy-based Transition Region (지역적 엔트로피 기반 전이 영역에서 퍼지 클러스터링 알고리즘을 이용한 Multi-Level Thresholding)

  • Oh, Jun-Taek;Kim, Bo-Ram;Kim, Wook-Hyun
    • The KIPS Transactions:PartB
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    • v.12B no.5 s.101
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    • pp.587-594
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    • 2005
  • This paper proposes a multi-level thresholding method for image segmentation using fuzzy clustering algorithm in transition region. Most of threshold-based image segmentation methods determine thresholds based on the histogram distribution of a given image. Therefore, the methods have difficulty in determining thresholds for real-image, which has a complex and undistinguished distribution, and demand much computational time and memory size. To solve these problems, we determine thresholds for real-image using fuzzy clustering algorithm after extracting transition region consisting of essential and important components in image. Transition region is extracted based on Inか entropy, which is robust to noise and is well-known as a tool that describes image information. And fuzzy clustering algorithm can determine optimal thresholds for real-image and be easily extended to multi-level thresholding. The experimental results demonstrate the effectiveness of the proposed method for performance.

Thermodynamic Approach to the Mixture Formation Process of Evaporative Diesel Spray (증발디젤분무의 혼합기 형성과정에 대한 열역학적 접근)

  • Yeom, Jeong-Kuk
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.33 no.3
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    • pp.201-206
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    • 2009
  • The focus of this work is placed on the analysis of the mixture formation process under the evaporative diesel-free spray conditions. In order to examine homogeneity of mixture within the vapor phase region of the injected spray, image analysis was carried out based on the entropy of statistical thermodynamics. As an experimental parameter, the injection pressure and ambient gas density were selected, and effects of the injection pressure and density variation of ambient gas on the mixture formation process in the evaporative diesel spray were investigated. In the case of application of the thermodynamic entropy analysis to evaporative diesel spray, the value of the dimensionless entropy always increases with increase in time from injection start. Consequently, the dimensionless entropy in the case of the higher injection pressure is higher than that of lower injection pressure during initial injection period.

Evaluation of Raingauge Networks in the Soyanggang Dam River Basin (소양강댐 유역의 강우관측망 적정성 평가)

  • Kim, Jae-Bok;Bae, Young-Dae;Park, Bong-Jin;Kim, Jae-Han
    • Proceedings of the Korea Water Resources Association Conference
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    • 2007.05a
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    • pp.178-182
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    • 2007
  • In this study, we evaluated current raingauge network of Soyanggang dam region applying spatial-correlation analysis and Entropy theory to recommend an optimized raingauge network. In the process of analysis, correlation distance of raingauge stations is estimated and evaluated via spatial-correlation method and entropy method. From this correlation distances, respective influencing radii of each dataset and each methods is assessed. The result of correlation and entropy analysis has estimated correlation distance of 25.546km and influence radius of 7.206km, deducing a decrease of network density from $224.53km^2$ to $122.47km^2$ which satisfy the recommended minimum densities of $250km^2$ in mountainous regions(WMO, 1994) and an increase of basin coverage from 59.3% to 86.8%. As for the elevation analysis the relative evaluation ratio increased from 0.59(current) to 0.92(optimized) resulting an obvious improvement.

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Noble Approach of Linear Entropy based Image Identification (영상 인식자를 위한 선형 엔트로피 기반 방법론)

  • Park, Je-Ho
    • Journal of the Semiconductor & Display Technology
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    • v.18 no.3
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    • pp.31-35
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    • 2019
  • Human beings have been fascinated by the applicability of the medium of photography since the device was first introduced in the thirteenth century to acquire images by attempting primitive and rudimentary approaches. In the 21st century, it has been developed as a wide range of technology that enables not only the application of artistic expression as a method of replacing the human-hand-painted screen but also the planar recording form in the format of video or image. It is more effective to use the information extracted from the image data rather than to use a randomly given file name in order to provide a variety of services in the offline or online system. When extracting an identifier from a region of an image, high cost cannot be avoided. This paper discusses the image entropy-based approach and proposes a linear methodology to measure the image entropy in an effort to devise a solution to this method.

The annual variation pattern and regional division of weather eatropy in South Korea (남한의 일기엔트로피의 연변화유형과 지역구분)

  • ;Park, Hyun-Wook
    • Journal of the Korean Geographical Society
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    • v.30 no.3
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    • pp.207-229
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    • 1995
  • The characteristics of weather and climate in South Korea has great influences on the annual variation pattern and the appearance of the prevailing weather. The purpose of this paper is to induce the quantity of the weather entropy and annual variation pattern using the information theory and the principal component analysis. And author tried to classify the region according to the variation of its space scale, The raw materials used for this study are the daily cloudiness and precipitation during the years 1990-1994 at 69 stations in South Korea. It is divided into four classes of fine, clear, cloudy and rainy. The rcsults of this study can be summarized as follows: 1. Thc characteristics of annual variation pattern of weather entropy can be chiefly divided into five categories and the accumulated contributory rate of these is 73.1%. 2. Annual variation pattern of the first principal component reaches smaller in May, April and September than national average, and becomes greater when the winter comes. This weather entropy's quantity(Rs1) is positive in most area to the western sife of Soback Mountains and negative in most seaside area to the eastern side of Soback Mountains. 3. The characteristics of annual variation pattern of the second principal component shows that the entropy is more smaller in summer than national average and the rest of seasons shows larger, especially in January, May and September. This weather entropy's quantity(Rs2) is positive in most Honam Inland area to the western side of Soback Mountains and negative in most Youngnam Inland area to the eastern side of Soback Mountains. 4. Eight type regions (S1-S11) are classified based on the occurrences of minimum weather entropy in South Korea, and annual variation pattern of weather entropy by principal component analysis may be classified into sixteen type regions (Rs1-Rs9). Putting these things together, South Korea can be classifieed into thirty one type regions (Rs1S7-Rs9S10).

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