• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.509-511
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• 2005

KOMPSAT -2 equipped with an optical telescope(MSC) will be launched in this year. It can take images of the earth with push-broom scanning at altitude 685Km. Its resolution is 1m in panchromatic channel with a swath width of 15 km After the MSC is tested and the performance is measured at instrument level, it is installed on satellite. The image passes through the electro-optical system, compression and storage unit and fmally downlink sub-systems. This integration procedure necessitates the functional test of all subsystems participating in the image chain. The objective of functional test at satellite level(Quick Look test) is to check the functionality of image chain by real target image. Collimated moving image is input to the EOS in order to simulate the operational environments as if KOMPSAT -2 is being operated in orbit. The image chain from EOS to data downlink subsystem will be verified through Quick Look test. This paper explains the Quick Look test of KOMPSAT -2 and compares the taken images with collimated input ones.

• Communications for Statistical Applications and Methods
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• 제10권2호
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• pp.325-332
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• 2003

This study was to develop a system for grading apples by their color using statistical image processing. T-test was used to detect edges in apple images and the chain code method was used for contour coding. The histogram and mean gray level of each RGB channel in a ring-shaped region was used to compare apple colors to reference apple color.

• Journal of Information Processing Systems
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• 제13권1호
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• pp.114-127
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• 2017

This paper proposes a color image coding algorithm based on shape-adaptive all phase biorthogonal transform (SA-APBT). This algorithm is implemented through four procedures: color space conversion, image segmentation, shape coding, and texture coding. Region-of-interest (ROI) and background area are obtained by image segmentation. Shape coding uses chain code. The texture coding of the ROI is prior to the background area. SA-APBT and uniform quantization are adopted in texture coding. Compared with the color image coding algorithm based on shape-adaptive discrete cosine transform (SA-DCT) at the same bit rates, experimental results on test color images reveal that the objective quality and subjective effects of the reconstructed images using the proposed algorithm are better, especially at low bit rates. Moreover, the complexity of the proposed algorithm is reduced because of uniform quantization.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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• pp.349-354
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• 1999

Electro-Optical Camera (EOC) is the main payload of the KOMPSAT-1 satellite to perform the mission of cartography that builds up a digital map of Korean territory including a digital terrain elevation map. This paper discusses the issues of the digital image simulation of EOC for the generation of EOC simulated scene as taken by EOC at 685km altitude on orbit. For the purpose, simulation work has been performed with the sensor models of EOC and the satellite platform motions models through image chain analysis from the illumination source (Sun) to a simulated image output in digital number. MODTRAN fur radiance calculation, MTF models of optics, detector and motions of EOC for system point spread function (PSF), and signal chain equations for digital number output are described. Several noise models of EOC are also considered. The final output is the EOC simulated image in digital number. The simulation technique can be used in several phase of a spaceborne electro-optical system development project, feasibility study phase, design, manufacturing, test phases, ground image processing phases, and so on.

• 한국복합재료학회:학술대회논문집
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• 한국복합재료학회 2005년도 추계학술발표대회 논문집
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• pp.107-110
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• 2005

In this study we investigated the shear and forming behavior of chain stitched multi-axial warp knitted fabric preform, so called non-crimp fabric (NCF). The picture frame test was performed to characterize the shear behavior of NCF and also provide material properties for the numerical simulation of its deformation behavior. The forming behavior of NCF with chain stitch were investigated using hemispherical forming tools. The experimental results show that processing conditions such as blank holder force (BHF) and preform shape are crucial to determining the forming behavior of NCF. For instance, an asymmetric formed shape, which is due to the stitches introduced to NCF, turns into a symmetric one as BHF increases. Furthermore the in-plane and out-of buckling (wrinkle), the severance of which were quantified using image processing method, decreases significantly as BHF increases.

• 응용통계연구
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• 제16권1호
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• pp.129-140
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• 2003

본 논문은 통계적 영상처리를 이용하여 과일 선별 시스템을 개발하고자 한다. 히스토그램으로부터 과일 영상의 색깔에 대한 분포를 파악하고 이 표본 위치문제에서 Wilcoxon 검정을 이용하여 에지를 검출한다. 체인코드로부터 과일 영상의 면적, 둘레, 장ㆍ단축의 길이와 원형도 등 기하학적 특성값을 얻는다. 우리는 과일에 대한 영상실험을 통하여 통계적 에지검출 방법에 토대를 둔 시스템과 기존의 Sobel 연산자에 토대를 둔 시스템과의 비교 분석한다.

• Agricultural and Biosystems Engineering
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• 제1권2호
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• pp.100-105
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• 2000

Quality sorting of cut flowers is very essential to increase the value of products. There are many factors that determine the quality of cut flowers such as length, thickness, and straightness of stem, and color and maturity of bud. Among these factors, the straightness of stem and the maturity of bud are generally considered to be more difficult to evaluate. A prototype grading and sorting machine for cut flowers was developed and tested for a rose variety. The machine consisted of a chain-drive feed mechanism, a pneumatic discharge system, and a grading system utilizing color image processing and neural network. Artificial neural network algorithm was utilized to grade cut roses based on the straightness of stem and maturity of bud. Test results showed 89% agreement with human expert for the straightness of stem and 90% agreement for the maturity of bud. Average processing time for evaluating straightness of the stem and maturity of the bud were 1.01 and 0.44 second, respectively. Application of neural network eliminated difficulties in determining criteria of each grade category while maintaining similar level of classification error.

• 한국콘텐츠학회논문지
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• 제15권2호
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• pp.433-443
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• 2015

최근 커피 시장은 초고속 성장을 거듭하면서 커피에 대한 소비가 증가하고 있다. 하지만 커피 전문점들이 우후죽순 생겨나면서 전문점 간 경쟁이 점점 치열해지고 있다. 그래서 커피 전문점들은 고객과의 장기적 관계를 유지하기 위해서 고객 충성도를 향상시키고자 노력하고 있다. 본 연구에서는 자의 기반 메커니즘과 구속 기반 메커니즘을 통합하여 고객들의 충성도 형성 메커니즘을 살펴보았다. 자의 기반 메커니즘으로 고객 만족을 고려하였으며, 구속 기반 메커니즘으로 전환 비용을 고려하였다. 고객 만족의 선행 요인으로 커피 품질, 서비스 품질, 가격 및 가치, 서비스 환경을 선정하였으며, 전환 비용의 선행 요인으로는 습관과 브랜드 이미지를 고려하였다. 제안한 연구 모형은 커피전문점을 방문하여 커피를 음용한 경험자 중 대학생 263명을 대상으로 검증되었다. 연구 분석 결과, 고객 만족과 전환 비용은 고객 충성도 분산의 66.1%를 설명해 주었다. 커피 전문점 품질 요인들은 모두 고객 만족에 유의한 영향을 미쳤다. 또한 습관과 브랜드 이미지는 전환 비용 형성에 중요한 역할을 담당하고 있음을 알 수 있었다.

• Journal of Biosystems Engineering
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• 제17권2호
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• pp.143-155
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• 1992

The aim of this study is to develop a general purpose algorithm for analyzing geometrical features of agricultural products and microscopic particles regardless of their numbers, shapes and positions with a computer vision system. Primarily, boundary informations of an image were obtained by Scan Line Coding and Scan & Chain Coding methods and then with these informations, geometrical features such as area, perimeter, lengths, widths, centroid, major and minor axes, equivalent circle diameter, number of individual objects, etc, were analyzed. The algorithms developed in this study was evaluated with test images consisting of a number of randomly generated ellipsoids or a few synthesized diagrams having different features. The result was successful in terms of accuracy.

• Korean Journal of Radiology
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• 제22권7호
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• pp.1213-1224
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• 2021

Objective: To develop a machine learning (ML) pipeline based on radiomics to predict Coronavirus Disease 2019 (COVID-19) severity and the future deterioration to critical illness using CT and clinical variables. Materials and Methods: Clinical data were collected from 981 patients from a multi-institutional international cohort with real-time polymerase chain reaction-confirmed COVID-19. Radiomics features were extracted from chest CT of the patients. The data of the cohort were randomly divided into training, validation, and test sets using a 7:1:2 ratio. A ML pipeline consisting of a model to predict severity and time-to-event model to predict progression to critical illness were trained on radiomics features and clinical variables. The receiver operating characteristic area under the curve (ROC-AUC), concordance index (C-index), and time-dependent ROC-AUC were calculated to determine model performance, which was compared with consensus CT severity scores obtained by visual interpretation by radiologists. Results: Among 981 patients with confirmed COVID-19, 274 patients developed critical illness. Radiomics features and clinical variables resulted in the best performance for the prediction of disease severity with a highest test ROC-AUC of 0.76 compared with 0.70 (0.76 vs. 0.70, p = 0.023) for visual CT severity score and clinical variables. The progression prediction model achieved a test C-index of 0.868 when it was based on the combination of CT radiomics and clinical variables compared with 0.767 when based on CT radiomics features alone (p < 0.001), 0.847 when based on clinical variables alone (p = 0.110), and 0.860 when based on the combination of visual CT severity scores and clinical variables (p = 0.549). Furthermore, the model based on the combination of CT radiomics and clinical variables achieved time-dependent ROC-AUCs of 0.897, 0.933, and 0.927 for the prediction of progression risks at 3, 5 and 7 days, respectively. Conclusion: CT radiomics features combined with clinical variables were predictive of COVID-19 severity and progression to critical illness with fairly high accuracy.