• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.221.1-221.1
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• 2012

The Korea Astronomy and Space Science Institute (KASI) is developing three 1.6m optical telescopes with $18k{\times}18k$ mosaic CCD cameras. These telescopes will be installed and operated at Chile, South Africa, and Australia for Korea Micro-lensing Telescope Network (KMTNet) project. The main scientific goal of the project is to discover earth-like extra-solar planets using the gravitational micro-lensing technique. To achieve the goal, each telescope at three sites will continuously monitor the specific region of Galactic bulge with 2.5 minute cadence for five years. Assuming 12 hour observation in maximum for a night, the amount of 200 GB file storage is required for one night observation at one observatory. If we consider the whole project period and the data processing procedure, a few PB class data storage, high-speed network, and high performance computers are essential. In this presentation, we introduce the KMTNet data management plan that handles gigantic data; raw image collecting, image processing, photometry pipeline, database archiving, and backup.

• Current Optics and Photonics
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• v.7 no.4
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• pp.435-442
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• 2023

These days, the size of a reflective telescope has been increasing for astronomical observation. An additional optical system usually assists a large ground telescope for image analysis or the compensation of air turbulence. To guide collimated light to the external optical system through a designated path, a coudé mirror is usually adopted. Including a collimator, a coudé mirror of a ground telescope is affected by gravity, depending on the telescope's pointing direction. The mirror surface is deformed by the weight of the mirror itself and its mount, which deteriorates the optical performance. In this research, we propose an optimization method for the coudé mirror assembly for a 1-m class ground telescope that minimizes the gravitational surface error (SFE). Here the mirror support positions and the sizes of the mount structure are optimized using finite element analysis and the response surface optimization method in both the horizontal and vertical directions, considering the telescope's altitude angle. Throughout the whole design process, the coefficients of the Zernike polynomials are calculated and their amplitude changes are monitored to determine the optimal design parameters. At the same time, the design budgets for the thermal SFE and the mass and size of the mount are reflected in the study.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.6
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• pp.413-421
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• 2015

Regularized Blind Deconvolution is a problem applicable in degraded images in order to bring the original image out of blur. Multichannel blind Deconvolution considered as an optimization problem. Each step in the optimization is considered as variable splitting problem using an algorithm called Alternating Minimization Algorithm. Each Step in the Variable splitting undergoes Augmented Lagrangian method (ALM) / Bregman Iterative method. Regularization is used where an ill posed problem converted into a well posed problem. Two well known regularizers are Tikhonov class and Total Variation (TV) / L2 model. TV can be isotropic and anisotropic, where isotropic for L2 norm and anisotropic for L1 norm. Based on many probabilistic model and Fourier Transforms Image deblurring can be solved. Here in this paper to improve the performance, we have used an adaptive regularization filtering and isotropic TV model Lp norm. Image deblurring is applicable in the areas such as medical image sensing, astrophotography, traffic signal monitoring, remote sensors, case investigation and even images that are taken using a digital camera / mobile cameras.

• Culinary science and hospitality research
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• v.7 no.3
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• pp.193-209
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• 2001

The result of this study suggests that students' perception of service value is related to functional value with regard to need and satisfaction, epistemic value, image, emotional value, functional value with regard to price and quality, and social value. Specifically female students give less importance to epistemic value than their male counterparts. Students in the 2nd grade gave less favorable scores to the functional value with regard to need and satisfaction, epistemic value, image, emotional value and functional value with regard to price and quality than students in the 1st grade. Students in the night class gave less scores to epistemic value and functional value with regard to price and quality than students in the day class. It is confirmed that the difference between groups by the period in school is in functional value with regard to need and satisfaction, image, emotional value, and functional value with regard to price and quality. And it is also revealed that these results are similar to the results of analysis by the grade. In conclusion college operators should not overemphasize that the department of Hotel culinary arts occupies the leading position of the culinary academic world in Korea and the firms of food service industry positively evaluate the department of Hotel culinary arts, and in order to cope with the rapidly changing environment of the culinary education consistent investment constant changes and of efforts should not be stopped. On one hand the teaching staff of the department of Hotel culinary arts should reconsider their original role, and need behavior and practice to fill their deficiency with steady efforts in terms of students' perceived service value. In addition the students of the department of Hotel culinary arts should not be shackled by the past tradition, should not take a pessimistic view of the present situation, should not take an optimistic view of the future, and should always cultivate their ability to provide for the future.

• Journal of the Korean Association of Geographic Information Studies
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• v.4 no.4
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• pp.1-7
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• 2001

Remotely sensed data is the most fundamental data in acquiring the GIS informations, and may be analyzed to extract useful thematic information. Multi-spectral classification is one of the most often used methods of information extraction. The actual multi-spectral classification may be performed using either supervised or unsupervised approaches. This paper analyze the effect of assigning clever initial values to image classes on the performance of parallelepiped classification algorithm, which is one of the supervised classification algorithms. First, we investigate the effect on serial computing model, then expand it on MIMD(Multiple Instruction Multiple Data) parallel computing model. On serial computing model, the performance of the parallel pipe algorithm improved 2.4 times at most and, on MIMD parallel computing model the performance improved about 2.5 times as clever initial values are assigned to image class. Through computer simulation we find that initial values of image class greatly affect the performance of parallelepiped classification algorithms, and it can be improved greatly when classes on both serial computing model and MIMD parallel computation model.

• Progress in Medical Physics
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• v.17 no.2
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• pp.77-82
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• 2006

The image display is an Important component of PACS and of medical digital imaging chain. Displayed image qualify is affected by the physical characteristics of display device, appropriate clinical settings and calibrations, and ambient lighting conditions. The performance of display systems is continuously degraded over time due to luminance deterioration and changes of clinical setting parameters. A routine QC is recommended because the performance of display systems is continuously degraded over time. Ten flat panel monochrome LCD display devices were included in the evaluation of the QC effect. The effect of QC on primary class LCD medical display devices for selected QC tests was evaluated by comparing the performances, luminance response, luminance dependencies, display resolution and display chromaticity in this study, of before and after the calibration procedures. The effects of the QC are significant to luminance response and luminance spatial dependencies test and the other side, are slight to the display resolution and display chromaticity test. A routine QC of display device is essential for the consistency of medical image display and presentation. The study of the QC effects of display devices will play an important role in practical QC procedures of display devices.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.17 no.3
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• pp.181-188
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• 2012

Despite the ecological importance of seagrass beds, their distributional information in Korean coastal waters is insufficient. Therefore, we used hydroacoustic system to collect accurate bathymetry and classification of seagrass, and Kompsat-2 (4 m spatial resolution) image for detection of seagrass beds at Deukryang Bay, Korea. The accuracy of Kompsat-2 image classification was evaluated using hydracoustic survey result using error matrix and Kappa value. The total area of seagrass beds from satellite image classification was underestimated compared to the hydroacoustic survey, estimated 3.9 and $4.5km^2$ from satellite image and hydroacoustic data, respectively. Nonetheless, the accuracy of Kompsat-2 image classification over hydroacoustic-based method showing 90% (Kappa=0.85) for the three class maps (seagrass, unvegetated seawater and aquaculture). The agreement between the satellite image classification and the hydroacoustic result was 77.1% (the seagrass presence/absence map). From our result of satellite image classification, Kompsat-2 image is suitable for mapping seagrass beds with high accuracy and non-destructive method. For more accurate information, more researches with a variety of high-resolution satellite image will be preceded.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.9
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• pp.37-49
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• 1992

The standard definition of computational vision is a set of inverse problems of recovering surfaces from images. Thus the common characteristics of the most early vision problems are ill-posed. The main idea for solving ill-posed problems is to restrict the class of admissible solutions by introducing suitable a priori knowledge. Standard regurarization methods lead to satisfactory solutions of early vision problems but cannot deal effectively and directly with a few general problems, such as discontinuity and fusion of information from multiple modules. In this paper, we discuss limitations of standard regularization theory and present new stochastic method. We will outline a rigorous approach to overcome part of ill-posedness of image restoration, edge detection, and stereo vision problems, based on Bayes estimation and MRF(Markov random field) model, that effectively deals with the problems. This result makes one hope that this framework could be useful in the solution of other vision problems.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.783-788
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• 2003

In this paper, we present a new approach to detect and recognize human face in the image from vision camera equipped on the mobile robot platform. Due to the mobility of camera platform, obtained facial image is small and pose-various. For this condition, new algorithm should cope with these constraints and can detect and recognize face in nearly real time. In detection step, ‘coarse to fine’ detection strategy is used. Firstly, region boundary including face is roughly located by dual ellipse templates of facial color and on this region, the locations of three main facial features- two eyes and mouth-are estimated. For this, simplified facial feature maps using characteristic chrominance are made out and candidate pixels are segmented as eye or mouth pixels group. These candidate facial features are verified whether the length and orientation of feature pairs are suitable for face geometry. In recognition step, pseudo-convex hull area of gray face image is defined which area includes feature triangle connecting two eyes and mouth. And random lattice line set are composed and laid on this convex hull area, and then 2D appearance of this area is represented. From these procedures, facial information of detected face is obtained and face DB images are similarly processed for each person class. Based on facial information of these areas, distance measure of match of lattice lines is calculated and face image is recognized using this measure as a classifier. This proposed detection and recognition algorithms overcome the constraints of previous approach [15], make real-time face detection and recognition possible, and guarantee the correct recognition irregardless of some pose variation of face. The usefulness at mobile robot application is demonstrated.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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• pp.1720-1728
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• 2022

The industrial 4.0 era has been opened with the development of artificial intelligence technology, and the realization of smart farms incorporating ICT technology is receiving great attention in the livestock industry. Among them, the quality management technology of livestock products and livestock operations incorporating computer vision-based artificial intelligence technology represent key technologies. However, the insufficient number of livestock image data for artificial intelligence model training and the severely unbalanced ratio of labels for recognizing a specific defective state are major obstacles to the related research and technology development. To overcome these problems, in this study, combining oversampling and adversarial case generation techniques is proposed as a method necessary to effectively utilizing small data labels for successful defect detection. In addition, experiments comparing performance and time cost of the applicable techniques were conducted. Through experiments, we confirm the validity of the proposed methods and draw utilization strategies from the study results.