• Journal of Broadcast Engineering
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• v.21 no.2
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• pp.272-275
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• 2016

This paper presents a method of single image dehazing and surface-based feature detection for remote sensing images. In the conventional dark channel prior (DCP) algorithm, the resulting transmission map invariably includes some block artifacts because of patch-based processing. This also causes image blur. Therefore, a refined transmission map based on a hidden Markov random field and expectation-maximization algorithm can reduce the block artifacts and also increase the image clarity. Also, the proposed algorithm enhances the accuracy of image matching surface-based features in an remote sensing image. Experimental results confirm that the proposed algorithm is superior to conventional algorithms in image haze removal. Moreover, the proposed algorithm is suitable for the problem of image matching based on feature extraction.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.650-655
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• 2001

Wind speeds can vary rapidly and wind turbines cannot easily follow these variations because of their inertia and aerodynamic characteristics. For maximum energy extraction. the turbine blades should operate at their optimum tip speed ratio, but with rapid changes in wind speed. this is usually not possible. To improve the energy extraction from turbulent wind, it is necessary to establish an effective measure of the high frequency component of the wind. and then to use this measure to optimise the operation of the turbine controller for maximum energy extraction. This paper presents an approach for combining readings from three anemometers into a composite wind speed measurement. and using this signal to control the operation of a permanent magnet generator to achieve maximum energy extraction. The method combines simulation and experimental investigations into a heuristic algorithm. and demonstrates its effectiveness with field trials.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.163-167
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• 2009

3D human body scan technique is known to be practically useful in industrial field as the technique becomes more precise and cheaper. Landmark extraction is essential for full utilization of the scan data. In this paper, we suggest an algorithm for automatic landmark extraction. For this purpose, we perform markerless matching to the target data using PCA analysis and quasi-Newton optimization. Landmarks are extracted from the topology of resulting body.

• 한국가시화정보학회:학술대회논문집
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• 2005.12a
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• pp.1-5
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• 2005

The digital HPTV velocity field measurement consists of four steps: recording, numerical reconstruction, particle extraction and velocity extraction. In the velocity extraction process, we improved PTV algorithm to extract the displacement of particle each placed in 3D space. Because a digital recording device was used, some factors such as a spatial resolution, numerical aperture, and particle concentration can affect the performance of the digital HPTV. Especially, a particle concentration ($C_{o}$) affected tile reconstruction efficiency in numerical reconstruction and particle extraction process. In this paper, the reconstruction efficiency was analyzed experimentally with different particle concentration. Optimal reconstruction efficiency was shown in the range of $C_{o}$=$13\∼15$ particles/$mm^{3}$.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.30 no.10 s.253
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• pp.929-934
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• 2006

The digital HPTV(holographic particle tracking velocimetry) velocity field measurement system consists of four steps: recording, numerical reconstruction, particle extraction and velocity extraction. In the velocity extraction process, we improved the two frame PTV algorithm to extract 3-D displacement information of each particle located in 3D space. Because a digital CCD camera was used, some factors such as spatial resolution, numerical aperture, and particle concentration influenced on the performance of the developed digital HPTV. Especially, the particle concentration $(C_o)$ affected the reconstruction efficiency and recovery ratio in the numerical reconstruction and particle extraction procedure. In this paper, the effect of particle concentration reconstruction efficiency and recovery ratio were analyzed experimentally. Optimal particle concentration was found to be in the range of $C_o=11{\sim}17\;particles/mm^3$.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.1
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• pp.154-160
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• 1995

Maps are one of the most complicated types of drawings. Drawing recognition technology is not yet sophisticated enough for automated map reading. To automatically extract a road map directly form more complicated topographical maps, a very complicated algorithm is needed, simce the image generally involves such complicated patterns as symbols, characters, residential sections, rivers,etc. This paper describes a new feature extraction method based on the human optical neural field. We apply this method to extract complete set of road segments from topographical maps. The proposed method successfully extract road segments from various areas.

• The Journal of Engineering Geology
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• v.30 no.4
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• pp.435-446
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• 2020

The use of groundwater in Korea has increased in recent years to the point where its extraction is restricted in times of drought. This work models the groundwater pumping field as a confined aquifer in a simplified simulation of groundwater flow. It proposes a genetic algorithm to maximize groundwater development using a conceptual model of a steady-state confined aquifer. Solving the groundwater flow equation numerically calculates the hydraulic head along the domain of the problem; the algorithm subsequently offers optimized pumping strategies. The algorithm proposed here is designed to improve a prior initial groundwater management model. The best solution is obtained after 200 iterations. The results compare the computing time for five simulation cases. This study shows that the proposed algorithm can facilitate better groundwater development compared with a basic genetic algorithm.

• The Transactions of the Korea Information Processing Society
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• v.1 no.4
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• pp.452-460
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• 1994

Maps are one of the most complicated types of drawings. Drawing recognition technology is not yet sophisticated enough for automated map reading To automatically extract a road map directly from more complicated topographical maps, a very complicated algorithm is needed, since the image generally involves such complicated patterns as symbols, characters, residential sections, rivers, railroads, etc. This paper describes a new feature extraction method based on the human optical neural field. We apply this method to extract complete set of road segments from topographical maps. The proposed method successfully extract road segments from various areas.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.3
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• pp.441-458
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• 1996

Many researches on feature recognition have been performed up to now, but the general solution for recognizing arbitrary features has not been developed. The most popular research area in feature recognition is automatic extraction of 2.5 dimensional features, because they are frequently used in manufacturing field. In this paper, a faster and more convenient 2.5 dimensional feature recognition algorithm is proposed using a new strategy which is quite different from the existing ones. The proposed algorithm takes process planning into consideration. The algorithm is implemented in C++. By applying the algorithm to practical complicate examples, we verify that the algorithm is working very well.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.29 no.1 s.232
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• pp.123-130
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• 2005

A digital in-line holographic particle image velocimetry (HPIV) which can be applied to measure three-dimensional velocity fields of turbulent flows was developed. There are three different implementation methods of HPIV: traditional film-based HPIV, intermediate HPIV and digital HPIV. The traditional film-based HPIV and intermediate HPIV method is rather troublesome to do experiments and takes long calculation time, compared with the digital HPIV, Configuration of the digital in-line HPIV is simple and the data processing routine is similar to conventional 2D PIV methods. The digital HPIV velocity field measurement consists of four steps: recording, numerical reconstruction, particle extraction and velocity extraction. In the velocity extraction process, we improved PTV algorithm to extract the displacement of particle each placed in 3D space. The developed digital in-line HPIV system was applied to a vertical jet flow. The 3D velocity vectors measured by the digital HPIV method in the near field are in a good agreement with 2D PIV results.