• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1690-1710
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• 2014

In this paper, we propose the rapid implementation of a 3-dimensional (3D) facial reconstruction from a single frontal face image and introduce a design for its application on a mobile device. The proposed system can effectively reconstruct human faces in 3D using an approach robust to lighting conditions, and a fast method based on a Canonical Correlation Analysis (CCA) algorithm to estimate the depth. The reconstruction system is built by first creating 3D facial mapping from a personal identity vector of a face image. This mapping is then applied to real-world images captured with a built-in camera on a mobile device to form the corresponding 3D depth information. Finally, the facial texture from the face image is extracted and added to the reconstruction results. Experiments with an Android phone show that the implementation of this system as an Android application performs well. The advantage of the proposed method is an easy 3D reconstruction of almost all facial images captured in the real world with a fast computation. This has been clearly demonstrated in the Android application, which requires only a short time to reconstruct the 3D depth map.

• Journal of Korean Society for Geospatial Information Science
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• v.12 no.2 s.29
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• pp.17-28
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• 2004

This study has tried to develop the modified DRASTIC Model by supplying the parameters, such as structural lineament density and land-use, into conventional DRASTIC model, and to predict the potential of groundwater contamination using GIS in Hwanam 2 District, Gyeonggi Province, Korea. Since the aquifers in Korea is generally through the joints of rock-mass in hydrogeological environment, lineament density affects to the behavior of groundwater and contaminated plumes directly, and land-use reflect the effect of point or non-point source of contamination indirectly. For the statistical analysis, lattice-layers of each parameter were generated, and then level of confidence was assessed by analyzing each correlation coefficient. Groundwater contamination potential map was achieved as a final result by comparing modified DRASTIC potential and the amount of pollutant load logically. The result suggest the predictability of contamination potential in a specified area in the respects of hydrogeological aspect and water quality.

• International Journal of Fluid Machinery and Systems
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• v.2 no.2
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• pp.165-171
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• 2009

We developed a 'multi-point vibration acceleration method' for accurately predicting the cavitation intensity in pumps. Pressure wave generated by cavitation bubble collapse propagates and causes pump vibration. We measured vibration accelerations at several points on a casing, suction and discharge pipes of centrifugal and mixed-flow pumps. The measured vibration accelerations scattered because the pressure wave damped differently between the bubble collapse location and each sensor. In a conventional method, experimental constants are proposed without evaluating pressure propagation paths, then, the scattered vibration accelerations cause the inaccurate cavitation intensity. In our method, we formulated damping rate, transmittance of the pressure wave, and energy conversion from the pressure wave to the vibration along assumed pressure propagation paths. In the formulation, we theoretically defined a 'pressure propagation coefficient,' which is a correlation coefficient between the vibration acceleration and the bubble collapse pressure. With the pressure propagation coefficient, we can predict the cavitation intensity without experimental constants as proposed in a conventional method. The prediction accuracy of cavitation intensity is improved based on a statistical analysis of the multi-point vibration accelerations. The predicted cavitation intensity was verified with the plastic deformation rate of an aluminum sheet in the cavitation erosion area of the impeller blade. The cavitation intensities were proportional to the measured plastic deformation rates for three kinds of pumps. This suggests that our method is effective for estimating the cavitation intensity in pumps. We can make a cavitation intensity map by conducting this method and varying the flow rate and the net positive suction head (NPSH). The map is useful for avoiding the operating conditions having high risk of cavitation erosion.

• Journal of Digital Convergence
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• v.16 no.1
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• pp.351-356
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• 2018

The aim of this study is to propose guidelines for bus-stop information design that is more congested with the advent of U-Shelter, via case studies and focus group interviews. First, the literature research explored the concept of information design and correlation of information design and route map. Second, raising problems and consider improvement plans through case study in korea, overseas. Finally, current information design was evaluated and user's requests were derived through focus group interview. The current information design had problems with lack of priority, information overlaying, and hard recognition. Priority shall be selected by bus route, direction of bus, arrival time, interval, and operating time, and information overlay can be reduced into one. Also visualize the connection and direction between the lines using schematic and two-dimensional lines and shapes for recognition. Through this study, it will be used as a reference material to help improve and develop the bus-stop information design.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.98.2-98.2
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• 2012

We firstly present the unified Far-UV continuum map of the Taurus-Auriga-Perseus (TPA) complex, one of the largest local associations of dark cloud located in (l, b)=([154,180], [-28, -2]), by merging both FIMS and GALEX. The FUV continuum map shows that dust extinction correlate well with the FUV around the complex. It shows strong absorption in FUV toward the dense Taurus cloud while it does not in California cloud. It turned out that it is related to the relative location of each cloud and Perseus OB2 association. We also present some results of dust scattering simulation based on Monte Carlo Radiative Transfer technique (MCRT). Through this dust scattering simulation, we have derived the scattering parameter for this region, albedo(a)=$0.42^{+0.05}{_{-0.05}}$, asymmetry factor(g)=$0.47^{+0.11}{_{-0.27}}$. The optical parameters we obtained seem reasonable compared to the theoretical model values ~0.40 and ~0.65 for the albedo and the phase function though the phase function is rather small. Using the result of simulation, we figured out the geometries of each cloud in the complex region, especially their distances and thicknesses. Our predictions from the results are in good agreement with the previous studies related to the TPA complex. For example, the Taurus cloud is within ~200pc from the Sun and the Perseus seems to be multi-layered, at least two. The California cloud is more distant than the other cloud on average at ~350 pc and Auriga cloud seems to be between the Taurus cloud and the eastern end of the California cloud. We figured out that across the TPA complex region, there might be some correlation between the LSR velocity and the distance to each cloud in the complex.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.13 no.6
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• pp.161-172
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• 2010

As the interest on biodiversity has increased around the world, researches about evaluating potential for habitat are also increasing to find and comprehend the valuable habitats. This study focus on comprehending the significance of stream in evaluating habitat's potential. The purpose of this study is to evaluate habitat potential with applying stream as a main variable, and to comprehend the relationship between the variables and habitat potential. Basin is a unit that has hydrological properties and dynamic interaction with ecosystem. Especially, biodiversity and suitability of habitat in basin area has direct correlation with stream. Existing studies also are proposing for habitat potential evaluation in basin unit, they applied forest, slope and road as main variables. Despite stream is considered the most important factor in basin area, researchers haven't applied stream as a main variable. Therefore, in this study, three variables that can demonstrate hydrological properties are selected, which are, riparian distance, stream order and land use disturbance, and evaluate habitat potential. Habitat potential is analyzed by using Maxent (Maximum entropy model), and vertebrate's presence data is used as dependent variables and stream order map and land cover map is used as base data of independent variables. As a result of analysis, habitat potential is higher at riparian and upstream area, and lower at frequently disturbed area. Result indicates that adjacent to stream, upstream, and less disturbed area is the habitat that vertebrate prefer. In particular, mammals prefer adjacent area of stream and forest and reptiles prefer upriver area. Birds prefer adjacent area of stream and midstream and amphibians prefer adjacent area of stream and upriver. The result of this research could help to establish habitat conservation strategy around basin unit in the future.

• Journal of Yeungnam Medical Science
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• v.39 no.1
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• pp.24-30
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• 2022

Background: Texture analysis has been used as a method for quantifying image properties based on textural features. The aim of the present study was to evaluate the usefulness of magnetic resonance imaging (MRI) texture analysis for the evaluation of viable ovarian tissue on the perfusion map of ovarian endometriosis. Methods: To generate a normalized perfusion map, subtracted T1-weighted imaging (T1WI), T1WI and contrast-enhanced T1W1 with sequences were performed using the same parameters in 25 patients with surgically confirmed ovarian endometriosis. Integrated density is defined as the sum of the values of the pixels in the image or selection. We investigated the parameters for texture analysis in ovarian endometriosis, including angular second moment (ASM), contrast, correlation, inverse difference moment (IDM), and entropy, which is equivalent to the product of area and mean gray value. Results: The perfusion ratio and integrated density of normal ovary were 0.52±0.05 and 238.72±136.21, respectively. Compared with the normal ovary, the affected ovary showed significant differences in total size (p<0.001), fractional area ratio (p<0.001), and perfusion ratio (p=0.010) but no significant differences in perfused tissue area (p=0.158) and integrated density (p=0.112). In comparison of parameters for texture analysis between the ovary with endometriosis and the contralateral normal ovary, ASM (p=0.004), contrast (p=0.002), IDM (p<0.001), and entropy (p=0.028) showed significant differences. A linear regression analysis revealed that fractional area had significant correlations with ASM (r²=0.211), IDM (r²=0.332), and entropy (r²=0.289). Conclusion: MRI texture analysis could be useful for the evaluation of viable ovarian tissues in patients with ovarian endometriosis.

• Korean Journal of Remote Sensing
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• v.39 no.6_3
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• pp.1707-1720
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• 2023

With the increase in satellite time series data, the utility of remote sensing data is growing. In the analysis of time series data, the relative positional accuracy between images has a significant impact on the results, making image registration essential for correction. In recent years, research on image registration has been increasing by applying deep learning, which outperforms existing image registration algorithms. To train deep learning-based registration models, a large number of image pairs are required. Additionally, creating a correlation map between the data of existing deep learning models and applying additional computations to extract registration points is inefficient. To overcome these drawbacks, this study developed a data augmentation technique for training image registration models and applied it to OffsetNet, a registration model that predicts the offset amount itself, to perform image registration for KOMSAT-2, -3, and -3A. The results of the model training showed that OffsetNet accurately predicted the offset amount for the test data, enabling effective registration of the master and slave images.

• The KIPS Transactions:PartB
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• v.11B no.3
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• pp.327-336
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• 2004

For visual inspection system in real industrial environment, it is one of most important tasks to design fast and stable pattern matching algorithm. This paper presents an edge-based point correlation algorithm avoiding full search in visual inspection system. Conventional algorithms based on NGC(normalized gray-level correlation) have to overcome some difficulties for applying to automated inspection system in factory environment. First of all, NGC algorithms need high time complexity and thus high performance hardware to satisfy real-time process. In addition, lighting condition in realistic factory environments if not stable and therefore intensity variation from uncontrolled lights gives many roubles for applying directly NGC as pattern matching algorithm in this paper, we propose an algorithm to solve these problems from using thinned and binarized edge data and skipping full point search with edge-map analysis. A point correlation algorithm with the thinned edges is introduced with image pyramid technique to reduce the time complexity. Matching edges instead of using original gray-level pixel data overcomes NGC problems and pyramid of edges also provides fast and stable processing. All proposed methods are preyed from experiments using real images.

• Journal of the Korean Geotechnical Society
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• v.38 no.9
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• pp.69-77
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• 2022

Several studies have been conducted to analyze the risk of ground subsidence occurring in urban areas. Recently, the correlation between the density of underground utilities (i.e., the quantity of buried utilities in the analysis area) and the recorded ground subsidence has been explored to analyze such risk through. Choi et al. (2021) proposed an algorithm to optimize the correlation between the ground subsidence and normalized linear density of underground pipelines. In this study, the optimization algorithm was modified for analysis based on the risk grade. The analysis results using the modified optimization algorithm were compared with the correlation analysis results between the density of underground utilities and recorded ground subsidence presented by Choi et al. (2021). Compared with Choi et al. (2021), three analysis results showed equal or higher accuracy in the correlation analysis with recorded ground subsidence according to risk grade. In particular, for R100, it was divided into five grades and compared with the ratio of the recorded ground subsidence that occurred in grades 4 or higher. As a result, Choi et al. (2021) showed that 86% of recorded ground subsidence occurred in grades 4 or higher, whereas this study showed 93%. It was confirmed that the accuracy of the modified optimization algorithm was improved. The modified optimization algorithm can be applied to develop a ground subsidence risk map for each grade in an urban area, which can be used as basic data for decision-making for underground utility maintenance.