• The KIPS Transactions:PartB
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• v.17B no.1
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• pp.15-22
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• 2010

Background generation is very important for accurate object tracking in video surveillance systems. Traditional background generation techniques have some problems with non-moving objects for longer periods. To overcome this problem, we propose a newbackground generation method using mean-shift and Fast Marching Method (FMM) to use pixel information along temporal and spatial dimensions. The mode of pixel value density along time axis is estimated by mean-shift algorithm and spatial information is evaluated by FMM, and then they are used together to generate a desirable background in the existence of non-moving objects during longer period. Experimental results show that our proposed method is more efficient than the traditional method.

• Nuclear Engineering and Technology
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• v.56 no.9
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• pp.3750-3757
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• 2024

Rapidly obtaining the coverage characteristics of leaching solution in In-situ Leaching Area of Sandstone Uranium Mines is a necessary condition for optimizing well locations reasonably. In the presented study, the improved algorithm of the Fast Marching Method (FMM) was studied for rapidly solving coverage characteristics to replace the groundwater numerical simulator. First, the effectiveness of the FMM was verified by simulating diffusion characteristics of the leaching solution in In-situ Leaching Area. Second, based on the radial flow pressure equation and the interaction mechanism of the front diffusion of production and injection well flow field, an improved FMM which is suitable for In-situ Leaching Mining, was developed to achieve the co-simulation of production and injection well. Finally, the improved algorithm was applied to engineering practice to guide the design and production. The results show that the improved algorithm can efficiently solve the coverage characteristics of leaching solution, which is consistent with those obtained from traditional numerical simulators. In engineering practice, the improved FMM can be used to rapidly analyze the leaching process, delineate Leaching Blind Spots, and evaluate the rationality of well pattern layout. Furthermore, it can help to achieve iterative optimization and rapid decision-making of production and injection well locations under largescale mining area models.

• Tunnel and Underground Space
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• v.18 no.4
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• pp.263-271
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• 2008

3D seismic tomography technique was assessed for applicability of developed 3D tomography algorithm based on Fresnel volume in the dam-planned area. Reconstructed 3D tomogram based on Fresnel volume and Fast Marching Method(FMM) reveals similar velocity structure to the other geotechnical survey results. With the correlation analysis between RMR data and seismic velocity information, it could provide reliable information of rock mass rate. The applicability of 3D seismic tomography was verified in this study. It would be expected to apply 3D tomography with new developed first arrival calculation and inversion algorithm to the engineering field economically.

• Tunnel and Underground Space
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• v.18 no.3
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• pp.202-213
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• 2008

In this study, theoretical approach of 3D seismic traveltime tomography was investigated. To guarantee the successful field application of 3D tomography, appropriate control of problem associated with blind zone is pre-requisite. To overcome the velocity distortion of the reconstructed tomogram due to insufficient source-receiver array coverage, the algorithm of 3D seismic traveltime tomography based on the Fresnel volume was developed as a technique of ray-path broadening. For the successful reconstruction of velocity cube, 3D traveltime algorithm was explored and employed on the basis of 2nd order Fast Marching Method(FMM), resulting in improvement of precision and accuracy. To prove the validity and field application of this algorithm, two numerical experiments were performed for globular and layered models. The algorithm was also found to be successfully applicable to field data.

• Korean Journal of Remote Sensing
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• v.37 no.4
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• pp.777-788
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• 2021

Since aerosol has a relatively short duration and significant spatial variation, satellite observations become more important for the spatially and temporally continuous quantification of aerosol. However, optical remote sensing has the disadvantage that it cannot detect AOD (Aerosol Optical Depth) for the regions covered by clouds or the regions with extremely high concentrations. Such missing values can increase the data uncertainty in the analyses of the Earth's environment. This paper presents a spatial gap-filling framework using a univariate statistical method such as DCT-PLS (Discrete Cosine Transform-based Penalized Least Square Regression) and FMM (Fast Matching Method) inpainting. We conducted a feasibility test for the hourly AOD product from AHI (Advanced Himawari Imager) between January 1 and December 31, 2019, and compared the accuracy statistics of the two spatial gap-filling methods. When the null-pixel area is not very large (null-pixel ratio < 0.6), the validation statistics of DCT-PLS and FMM techniques showed high accuracy of CC=0.988 (MAE=0.020) and CC=0.980 (MAE=0.028), respectively. Together with the AI-based gap-filling method using extra explanatory variables, the DCT-PLS and FMM techniques can be tested for the low-resolution images from the AMI (Advanced Meteorological Imager) of GK2A (Geostationary Korea Multi-purpose Satellite 2A), GEMS (Geostationary Environment Monitoring Spectrometer) and GOCI2 (Geostationary Ocean Color Imager) of GK2B (Geostationary Korea Multi-purpose Satellite 2B) and the high-resolution images from the CAS500 (Compact Advanced Satellite) series soon.