• 제목/요약/키워드: Classification index

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GLCM 기반 UAV 영상의 감독분류를 이용한 저수구역 내 농경지 탐지 (Detection of Cropland in Reservoir Area by Using Supervised Classification of UAV Imagery Based on GLCM)

  • 김규문;최재완
    • 한국측량학회지
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    • 제36권6호
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    • pp.433-442
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    • 2018
  • 저수구역은 계획된 홍수위에 의하여 둘러싸인 지역 혹은 댐의 계획된 홍수위 내에 있는 지역으로 정의된다. 본 연구에서는 저수구역 내 농경지를 탐지하기 위하여, 대표적인 기계학습 기법인 RF (Random Forest) 기반의 감독 분류 방법을 적용하였다. 저수구역 내의 농경지를 효과적으로 분류하기 위하여, 질감정보를 정량화하기 위한 대표적인 기법인 GLCM (Gray Level Co-occurrence Matrix)과 NDWI (Normalized Difference Water Index), NDVI (Normalized Difference Vegetation Index)를 추가적인 입력자료로 활용하였다. 특히, 질감정보를 생성하는데 사용된 윈도우 크기가 농경지의 분류 정확도에 미치는 영향을 분석하여, 저수구역 내의 농경지를 효과적으로 분류하기 위한 방법론을 제시하였다. 실험결과, UAV 영상을 이용한 분류결과를 통하여 취득된 다중분광영상과 NDVI, NDWI, GLCM 영상들을 이용하여 저수구역 내의 농경지를 효과적으로 탐지할 수 있음을 확인하였다. 또한, GLCM의 윈도우 크기가 분류정확도를 향상시키기 위한 중요한 변수임을 확인하였다.

비만 판정지수에 의한 여대생의 체형분류 및 체형인지도 (Classification of the Somatotype by Obesity Indexes and Body Cognition of Female College Students)

  • 성민정;김희은
    • 한국의류산업학회지
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    • 제3권3호
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    • pp.227-234
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    • 2001
  • The purpose of this study was to classify real somatotype by their obesity degree and to investigate cognitive somatotype by their body consciousness in female college students. The subjects were 172 female college students aged from 19 to 23 living in Taegu. Average height of the subjects was 161.33 em, weight was 52.49 kg, Rohrer Index was 125.33, BMI was 20.18, Vervaeck Index was 84.03, and percentage of body fat was 26.07. In classification of the subjects by 3 body indexes, lean figure took 37.79~50.00%, normal figure took 45.35~54.65%, and obese figure took 4.65~8.14% and in classification of the subjects by percentage of body fat was, lean figure took 38.95%, normal figure took 46.51%, and obese figure took 14.54%. In consciousness and satisfaction about body parts, the subjects recognized that their girth items were 'thick', length items were 'short', and weight was 'heavy'. Also they generally preferred slender and long body.

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Evaporative Stress Index (ESI)의 국내 가뭄 심도 분류 기준 제시 (Percentile Approach of Drought Severity Classification in Evaporative Stress Index for South Korea)

  • 이희진;남원호;윤동현;홍은미;김태곤;박종환;김대의
    • 한국농공학회논문집
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    • 제62권2호
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    • pp.63-73
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    • 2020
  • Drought is considered as a devastating hazard that causes serious agricultural, ecological and socio-economic impacts worldwide. Fundamentally, the drought can be defined as temporarily different levels of inadequate precipitation, soil moisture, and water supply relative to the long-term average conditions. From no unified definition of droughts, droughts have been divided into different severity level, i.e., moderate drought, severe drought, extreme drought and exceptional drought. The drought severity classification defined the ranges for each indicator for each dryness level. Because the ranges of the various indicators often don't coincide, the final drought category tends to be based on what the majority of the indicators show and on local observations. Evaporative Stress Index (ESI), a satellite-based drought index using the ratio of potential and actual evaporation, is being used as a index of the droughts occurring rapidly in a short period of time from studies showing a more sensitive and fast response to drought compared to Standardized Precipitation Index (SPI), and Palmer Drought Severity Index (PDSI). However, ESI is difficult to provide an objective drought assessment because it does not have clear drought severity classification criteria. In this study, U.S. Drought Monitor (USDM), the standard for drought determination used in the United States, was applied to ESI, and the Percentile method was used to classify drought categories by severity. Regarding the actual 2017 drought event in South Korea, we compare the spatial distribution of drought area and understand the USDM-based ESI by comparing the results of Standardized Groundwater level Index (SGI) and drought impact information. These results demonstrated that the USDM-based ESI could be an effective tool to provide objective drought conditions to inform management decisions for drought policy.

Rotation Invariant Histogram of Oriented Gradients

  • Cheon, Min-Kyu;Lee, Won-Ju;Hyun, Chang-Ho;Park, Mignon
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제11권4호
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    • pp.293-298
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    • 2011
  • In this paper, we propose a new image descriptor, that is, a rotation invariant histogram of oriented gradients (RIHOG). RIHOG overcomes a disadvantage of the histogram of oriented gradients (HOG), which is very sensitive to image rotation. The HOG only uses magnitude values of a pixel without considering neighboring pixels. The RIHOG uses the accumulated relative magnitude values of corresponding relative orientation calculated with neighboring pixels, which has an effect on reducing the sensitivity to image rotation. The performance of RIHOG is verified via the index of classification and classification of Brodatz texture data.

GENERATION OF AN IMPERVIOUS MAP BY APPLYING TASSELED-CAP ENHANCEMENT USING KOMPSAT-2 IMAGE

  • Koh, Chang-Hwan;Ha, Sung-Ryong
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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    • pp.378-381
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    • 2008
  • The regulating and relaxing targets in the Land Use Regulation and Total Maximum Daily Loads are influenced by Land cover information. For the providing more accurate land information, this study attempted to generate an impervious surface map using KOMPSAT-2 image which a Korea manufactured high resolution satellite image. The classification progress of this study carried out by tasseled-cap spectral enhancement through each class extraction technique neither existing classification method. KOMPSAT-2 image of this study is enhanced by Soil Brightness Index(SBI), Green vegetation Index(GVI), None-Such wetness Index(NWI). Then ranges of extracted each index in enhanced image are determined. And then, Confidence Interval of classes was determined through the calculating Non-exceedance Probability. Spectral distributions of each class are changed according to changing of Control coefficient(${\alpha}$) at the calculated Non-exceedance Probability. Previously, Land cover classification map was generated based on established ranges of classes, and then, pervious and impervious surface was reclassified. Finally, impervious ratio of reclassified impervious surface map was calculated with blocks in the study area.

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물산업 시장과 기술 비교분석 (A comparative analysis on market and technology in water industry)

  • 박임수
    • 상하수도학회지
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    • 제35권6호
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    • pp.437-454
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    • 2021
  • This study investgates Korean water technology through the water market perspective and analyses its competitiveness. Based on the water technology classification, water technology competitiveness is analysed through the technological influence index and market dominance index which are based on the extracted water technology patents from the US, Europe, Korea, and Japan for the last decade. As a result, the Korean water technology patents were lack in influence and competitiveness in global market considering the large volume of patents. There are two most tech-influential industries in Korea; manufacturing industry consisting pipes, sterilization, disinfection, and advanced water purification equipment, and construction industry including seawater desalination and water resource development. Due to the domestic usage of the patents, the Korean water technology patents scored low in global market PFS(Patent Family Size) index compared to their CPP(Cites Per Patent) index. The study is meaningful in a way that the analysis on Korean water technology competitiveness using water technology classification system and patent analysis was conducted based on the perspective of the global water market.

고해상도 영상의 분류결과 개선을 위한 최적의 Shape-Size Index 추출에 관한 연구 (A Study on Optimal Shape-Size Index Extraction for Classification of High Resolution Satellite Imagery)

  • 한유경;김혜진;최재완;김용일
    • 대한원격탐사학회지
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    • 제25권2호
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    • pp.145-154
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    • 2009
  • 고해상도 위성영상이 갖는 공간 객체의 복잡성과 다양성에 의해 기존 중 저해상도 영상에서 사용하던 분류 방식을 고해상도 영상에 그대로 적용하기에는 한계가 있다. 이러한 문제를 극복하기 위하여 영상의 공간적인 특성을 추가적으로 추출하여 분광정보와 결합하여 분류를 수행하는 방식의 연구가 진행되고 있다. 본 연구의 목적은 고해상도 영상의 분류정확도를 개선하기 위하여 새로운 공간 개체(spatial feature)인 SSI(Shape-Size Index)를 제안하는데 있다. SSI feature는 영역 확장(Region Growing) 기반의 영상 분할(Image Segmentation)을 수행한 후, 세그먼트 내에 공간 속성값을 할당하여 공간정보를 추출한다. 추출된 공간정보를 고해상도 영상의 다중분광 밴드와 결합하여 Support Vector Machine(SVM)을 이용한 분류를 수행하였다. SSI를 구성하는데 필요한 두 매개변수인 분할변수와 가중치변수의 최적값을 얻기 위해서 고해상도 위성영상인 KOMFSAT-2와 QuickBird-2에 반복적으로 적용하였다. 결과적으로 고해상도 영상의 공간특성을 표현하는데 적합한 매개변수를 통하여 도출된 SSI와 고해상도 분광 밴드를 결합하여 분류를 수행한 결과가 분광밴드만을 이용하여 분류를 수행한 결과에 비해 높은 분류정확도를 도출함을 확인하였다.

Alsat-2B/Sentinel-2 Imagery Classification Using the Hybrid Pigeon Inspired Optimization Algorithm

  • Arezki, Dounia;Fizazi, Hadria
    • Journal of Information Processing Systems
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    • 제17권4호
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    • pp.690-706
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    • 2021
  • Classification is a substantial operation in data mining, and each element is distributed taking into account its feature values in the corresponding class. Metaheuristics have been widely used in attempts to solve satellite image classification problems. This article proposes a hybrid approach, the flower pigeons-inspired optimization algorithm (FPIO), and the local search method of the flower pollination algorithm is integrated into the pigeon-inspired algorithm. The efficiency and power of the proposed FPIO approach are displayed with a series of images, supported by computational results that demonstrate the cogency of the proposed classification method on satellite imagery. For this work, the Davies-Bouldin Index is used as an objective function. FPIO is applied to different types of images (synthetic, Alsat-2B, and Sentinel-2). Moreover, a comparative experiment between FPIO and the genetic algorithm genetic algorithm is conducted. Experimental results showed that GA outperformed FPIO in matters of time computing. However, FPIO provided better quality results with less confusion. The overall experimental results demonstrate that the proposed approach is an efficient method for satellite imagery classification.

뇌파의 한의학적 진단 지표로의 활용 방안에 대한 연구초안 (The methodology on the application of EEG as a diagonostic measures in Korean Traditional Medicine)

  • 서영효;김경철;김보경
    • 동의신경정신과학회지
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    • 제18권1호
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    • pp.37-61
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    • 2007
  • Objective : By examining EEG status in Korean Traditional Medicine (KTM) from the viewpoint of 'form-qi theory(形氣論)', We wish to prepare for the fundamentals of applicability of KTM diagnoses to EEG. In addition, through reinterpretation of existing Western Medicine reports from the viewpoint of KTM, We tried to find out interrelationship between them. Method : In this paper, a methodology applicable to KTM diagnoses of EEG is presented from the EEG features in waveform characteristics, personalized diversity, and cognitive activity reflection. Results : Frequency bands are assigned to corresponding one of the eight trigrams in terms of yin/yang balance, which is analogous with EEG spectrum analysis mostly used in EEG quantification. The amplitude ratio of each EEG for each frequency band gives meaningful index numbers which can be used in EEG data interpretation, and every index number is named after the sixty four hexagrams. These approaches are adopted through both '4-band classification system and '6-band classification system', and applied to pre-existing reported EEG data obtained from normal adults. These analyses show that changes and distribution pattern in the index numbers are observed as a whole on both left-right line and front-back line connecting EEG measurement cephalic electrodes. And differences in distribution pattern of three index numbers deduced from '6-band classification system' are discussed according to constitution. Conclusion : The index numbers introduced here, which are the spectral power ratio for each EEG, are based on KTM yin/yang balance. These index numbers vary according to cephalic location, so its application in terms of traditional meridian theory is strongly expected. The index number distribution also shows different patterns according to constitution.

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임상 분류 정확도 향상을 위한 영상 알고리즘 변별력 실증 연구 -KOMPSAT-MSC를 이용한 경주지역을 대상으로- (An Empirical Study on Discrimination of Image Algorithm for Improving the Accuracy of Forest Type Classification -Case of Gyeongju Area Using KOMPSAT-MSC Image Data-)

  • 조윤원;김성재;조명희
    • 대한공간정보학회지
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    • 제17권2호
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    • pp.55-60
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    • 2009
  • 본 연구에서는 경주시 내남면을 대상으로 KOMPSAT-2 MSC(Multi Spectral Camera) 영상(2007.06.12)을 기반으로 NDVI(Normalized Difference Vegetation Index)와 TCT(Tasseled-Cap Transformation) 영상 알고리즘을 적용하여 DN 분포도를 작성 하였다. NDVI 및 TCT DN 분포도와 산림 현장 조사 결과와의 비교 분석을 통하여 임상 분류 정확도 향상을 위한 영상 알고리즘 변별력 분석을 수행하고 마지막으로 현장조사 자료와의 중첩 분석을 통하여 임상분류 정확성을 검증 하였다. 본 연구를 통하여 KOMPSAT-2 MSC 영상을 이용하여 임상 분류 자동화 실용성에 대한 검토와 정밀 산림 임상도 제작과정에서 저비용 고효율성을 기대할 수 있으리라 사료된다.

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