• Computers and Concrete
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• v.33 no.5
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• pp.481-496
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• 2024

Internal erosion around pipes can lead to the failure of earth dams through various mechanisms. This study investigates the displacement patterns in earth dam models under three different failure modes due to internal erosion, using digital image correlation (DIC) methods. Three failure modes—erosion along a pipe (FM1), pipe leakage leading to soil erosion (FM2), and erosion in a pipe due to defects (FM3)—are analyzed using two- and three-dimensional image- processing techniques. The internal displacement of the cross-sectional area and the surface displacement of the downstream slope in the dam models are monitored using an image acquisition system. Physical model tests reveal that FM1 exhibits significant displacement on the upper surface of the downstream slope, FM2 shows focused displacement around the pipe defect, and FM3 demonstrates increased displacement on the upstream slope. The variations in internal and surface displacements with time depend on the segmented area and failure mode. Analyzing the relationships between internal and surface displacements using Pearson correlation coefficients reveals various displacement patterns for the segmented areas and failure modes. Therefore, the image-based characterization methods presented in this study may be useful for analyzing the displacement distribution and behavior of earth dams around pipes, and further, for understanding and predicting their failure mechanisms.

• Journal of Korean Society of Rural Planning
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• v.10 no.2 s.23
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• pp.35-42
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• 2004

This study aimed at establishing the multi-ranged approach on data acquisition technique for rural landscape planning, which tried categorization, grading and transferring of landscape elements in the more detailed level. For the systematic management of database for the topographic informations in the village level, a kind of the aerial photographing techniques with UAV(Unmanned Aerial Vehicle) was used and its resultant data for the landscape simulation of the rural village, which in turn helped the convenient approach to understanding of its comprehensive spatial structure. The image data from aerial photography was systematically processed through; First, after revision of the distorted one, the image map was adjusted with the topographical and cadastral maps. Second, the farm houses and buildings, and other facilities difficult to find out in the topographical map was digitally read from the adjusted image. The topographical landscape view of rural village was simulated on the base of DEM(Digital Elevation Model) and the 3-dimensional shapes of farm houses and buildings were automatically modelled using the input system developed by the author. In conclusion, the aerial image information adjusted with the edited maps could give more intuitive and detailed villagescape than the ordinary one and through landscape simulation of the rural village, its topography, features of houses/buildings and spatial distribution of land uses were effectively reproduced. And, by the linkage between field survey and photographed/simulated results of the typical landscape elements using hyper-link method, it would be expected to develop as an effective visualization technique of rural landscape.

• Journal of Information Processing Systems
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• v.5 no.2
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• pp.41-68
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• 2009

Face recognition presents a challenging problem in the field of image analysis and computer vision, and as such has received a great deal of attention over the last few years because of its many applications in various domains. Face recognition techniques can be broadly divided into three categories based on the face data acquisition methodology: methods that operate on intensity images; those that deal with video sequences; and those that require other sensory data such as 3D information or infra-red imagery. In this paper, an overview of some of the well-known methods in each of these categories is provided and some of the benefits and drawbacks of the schemes mentioned therein are examined. Furthermore, a discussion outlining the incentive for using face recognition, the applications of this technology, and some of the difficulties plaguing current systems with regard to this task has also been provided. This paper also mentions some of the most recent algorithms developed for this purpose and attempts to give an idea of the state of the art of face recognition technology.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1206-1208
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• 2003

The extraction of earthquake damage from remote sensed imagery requires high spatial resolution and temporal effectiveness of acquisition of imagery. The analog photographs and visual interpretation were taken traditionally. Now it is possible to acquire damage information from many commercial high resolution RS satellites. The key techniques are processing velocity and precision. The authors developed the automatic / semiautomatic image process techniques including feature enhancement, and classification, designed the emergency Earthquake Damage and Losses Evaluate System based on Remote Sensing (RSEDLES). The paper introduced the functions of RSEDLES as well as its application to the earthquakes occurred recently.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.2
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• pp.60-67
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• 2007

This paper describes the development of on-line computer vision laboratories to teach the detailed image processing and pattern recognition techniques. The computer vision laboratories include distant image acquisition method, basic image processing and pattern recognition methods lens and light, and communication. This study introduces a case study that teaches computer vision in distance learning. environment. It shows a schematic of a distant teaming workstation and contents of laboratories with image processing examples. The study focus more on the contents of the vision Labs rather than internet application method. The study proposes the ways to improve the on-line computer vision laboratories and includes the further research perspectives.

• Journal of Ocean Engineering and Technology
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• v.31 no.1
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• pp.60-68
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• 2017

In this study, we analyzed the real time video image obtained from the video monitoring system to grasp the shoreline, beach width, and area change of Haeundae beach. The video monitoring techniques enabled continuous monitoring for a long period at a much lower cost than general survey methods. It was possible to grasp quantitative beach variation characteristics of Haeundae beach through image acquisition, rectification, and image processing of video images. According to the monitoring results, the erosion rate of Haeundae beach in spring and summer was -19.8% in 2014 and -6.7% in 2015. The erosion rate in 2016 was -6.4%, which showed that the erosion rate in spring and summer continued to decrease. In particular, the influence of the erosion at the time of typhoon CHABA was revealed to be smaller than in the past. It can be concluded that these variations were due to beach width expansion by beach nourishment and the installation of submerged breakwaters.

• Journal of The Korean Astronomical Society
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• v.38 no.4
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• pp.445-462
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• 2005

In a companion paper, we have presented so-called Spatio-Spectral Maximum Entropy Method (SSMEM) particularly designed for Fourier-Transform imaging over a wide spectral range. The SSMEM allows simultaneous acquisition of both spectral and spatial information and we consider it most suitable for imaging spectroscopy of solar microwave emission. In this paper, we run the SSMEM for a realistic model of solar microwave radiation and a model array resembling the Owens Valley Solar Array in order to identify and resolve possible issues in the application of the SSMEM to solar microwave imaging spectroscopy. We mainly concern ourselves with issues as to how the frequency dependent noise in the data and frequency-dependent variations of source size and background flux will affect the result of imaging spectroscopy under the SSMEM. We also test the capability of the SSMEM against other conventional techniques, CLEAN and MEM.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.6 no.1
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• pp.9-15
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• 2010

This paper describes the Visual Tool for automatic ultrasonic examination that is under developing as a part of the project for development of automatic ultrasonic wave acquisition and analysis program. This tool that is supported by various image processing techniques will be adopted to detect the flaws in the component and piping welds in NPP. Visual Tool will enhance the integrity of nuclear power plant. The object of this paper is to address the Visual Tool which is developing for automatic ultrasonic inspection of welds in NPP.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.280-282
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• 2003

The downlink data rates of the space-born payloads such as high-resolution optical cameras, synthetic aperture radars (SAR) and hyper-spectral sensors are being rapidly increased. For example, the image transmission rates of KOMPSAT-2 MSC(Multi-Spectral Camera) is 320Mbps even if on-board image compression scheme is used.[1] In the near future, the data rates are expected to be a level 500${\sim}$600Mbps because the required resolution will be higher and the swath width will be increased. This paper describes many techniques they enable 500Mbps data receiving and archiving system.

• Journal of IKEEE
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• v.22 no.4
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• pp.948-952
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• 2018

Haze removal is an object of scientific desire due to its various practical applications. Existing algorithms are founded upon histogram equalization, contrast maximization, or the growing trend of applying machine learning in image processing. Since machine learning-based algorithms solve problems based on the data, they usually perform better than those based on traditional image processing/computer vision techniques. However, to achieve such a high performance, one of the requisites is a large and reliable training database, which seems to be unattainable owing to the complexity of real hazy and haze-free images acquisition. As a result, researchers are currently using the synthetic database, obtained by introducing the synthetic haze drawn from the standard uniform distribution into the clear images. In this paper, we propose the enhanced equidistribution, improving upon our previous study on equidistribution, and use it to make a new database for training machine learning-based haze removal algorithms. A large number of experiments verify the effectiveness of our proposed methodology.