• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.41-46
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• 2006

This paper describes a marine watch system on a ship, which is aided by an image processing method. The system detects other ships through a navigational image sequence to prevent oversights, and it measures their bearings to maintain their movements. The proposed method is described, the detection techniques and measurement of bearings techniques are derived, and the results have been reported. The image is divided into small regions on the basis of the brightness value and then labeled. Each region is considered as a template. A template is assumed to be a ship. Then, the template is compared with frames in the original image after a selected time. A moving vector of the regions is calculated using an Excel table. Ships are detected using the characteristics of the moving vector. The video camera captures 30 frames per second. We segmented one frame into approximately 5000 regions; from these, approximately 100 regions are presumed to be ships and considered to be templates. Each template was compared with frames captured at 0.33 s or 0.66 s. In order to improve the accuracy, this interval was changed on the basis of the magnification of the video camera. Ships’ bearings also need to be determined. The proposed method can measure the ships’ bearings on the basis of three parameters: (1) the course of the own ship, (2) arrangement between the camera and hull, and (3) coordinates of the ships detected from the image. The course of the own ship can be obtained by using a gyrocompass. The camera axis is calibrated along a particular direction using a stable position on a bridge. The field of view of the video camera is measured from the size of a known structure on the hull in the image. Thus, ships’ bearings can be calculated using these parameters.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.2
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• pp.239-245
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• 2020

Recently, BIM (Building Information Modeling) are widely being utilized in Construction industry. However, most structures that have been constructed in the past do not have BIM. For structures without BIM, the use of SfM (Structure from Motion) techniques in the 2D image obtained from the camera allows the generation of 3D model point cloud data and BIM to be established. However, since these generated point cloud data do not contain semantic information, it is necessary to manually classify what elements of the structure. Therefore, in this study, deep learning was applied to automate the process of classifying structural components. In the establishment of deep learning network, Inception-ResNet-v2 of CNN (Convolutional Neural Network) structure was used, and the components of bridge structure were learned through transfer learning. As a result of classifying components using the data collected to verify the developed system, the components of the bridge were classified with an accuracy of 96.13 %.

• Journal of the Korean Institute of Landscape Architecture
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• v.27 no.4
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• pp.101-107
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• 1999

In 1994, Songbuk-gu Office of Seoul held a design competition for Miarigogae-Park, Miarigogae has a special sense of place. It was a place where bararians had crossed the boundary to this country during the Manchu war of 1636. It was a public cemetery where only Koreans had been buried under the rule of Japanese imperialism. It was a place where national patriots had been kidnapped to the North during the Korean War. It's sorrows have been sung in the name of song-'Danjangeui-Miarigogae'(one of the most popular song in Korea). It's sense of place has been kept in every Korean people's mind in the form on 'non-physical image'. Even though, the site itself was a small space - only 1000㎡, the meaning of park-making was very significant. It meant that it would create a physical 'setting' to express the sense of place which has been existed only in our mind as a form of 'non-physical image'. In the winning scheme proposed by the author, the sense of place of Miarigogae was expressed in the form of 'castle walls' which could be easily come into everyone's mind as an image of war. The scope of work also included a crossing bridge and symbolic features. It was meaningful that a landscape architect won the competition including on those items which were not usually handled in pure landscape architectural offices. The purpose of this paper was to articulate the concept of the winning entry in detail and to describe how the concept actualized in reality.

• The Journal of Korean Institute for Practical Engineering Education
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• v.3 no.1
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• pp.143-148
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• 2011

In this study, the damage to the bridge structure such as the crack and water leakage was assessed due to the increase of the vehicle load and traffic on the roads. In order to make this into the database, as a part of the automation system development for the bridge maintenance, the students themselves designed and developed their own inspection robotic system based on the idea of robots currently being developed overseas. Its field testing was conducted and its applicability assessed. During the design and fabrication, its connection to the details of the unit course taken in the undergraduate level was focused. In terms of new product development, the field application was possible due to the support of the academic-industrial cooperation firms. Furthermore, through the survey of the students, the improvements in the practical skills of the students who participated in this development process was affirmed.

• Smart Structures and Systems
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• v.22 no.2
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• pp.209-221
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• 2018

Efflorescence is a phenomenon primarily caused by a carbonation process in concrete structures. Efflorescence can cause concrete degradation in the long term; therefore, it must be accurately assessed by proper inspection. Currently, the assessment is performed on the basis of visual inspection or image-based inspection, which may result in the subjective assessment by the inspectors. In this paper, a novel approach is proposed for the objective and quantitative assessment of concrete efflorescence using hyperspectral imaging (HSI). HSI acquires the full electromagnetic spectrum of light reflected from a material, which enables the identification of materials in the image on the basis of spectrum. Spectral angle mapper (SAM) that calculates the similarity of a test spectrum in the hyperspectral image to a reference spectrum is used to assess efflorescence, and the reference spectral profiles of efflorescence are obtained from theUSGS spectral library. Field tests were carried out in a real building and a bridge. For each experiment, efflorescence assessed by the proposed approach was compared with that assessed by image-based approach mimicking conventional visual inspection. Performance measures such as accuracy, precision, and recall were calculated to check the performance of the proposed approach. Performance-related issues are discussed for further enhancement of the proposed approach.

• Journal of the Korean Geosynthetics Society
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• v.16 no.4
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• pp.177-190
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• 2017

This paper presents the results of an experimental study on the effect of large underground station construction method under an existing pile supported bridge using reduced-scale model tests. A series of tests were conducted on design alternatives using 1g models for different design options for which tunnel structures were created considering the similitude law. Deformation fields obtained using the PIV analysis and LVDTs together with strains in tunnel structures were used to investigate the effect of the construction methods on the pile supported bridge. The results of the tests demonstrated that the pipe roof structure is more efficient in limiting the ground deformation as well as the settlement of bridge foundation than a 2-Arch tunnel. It is also shown that the PIV analysis can be effectively used in analyzing ground tunneling induced ground movement for cases in which a construction sequence governs ground movement.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.5
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• pp.330-335
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• 2017

This study applied SONAR(Sound Navigation And Ranging) to the inspection and evaluation of underwater structures. Anactual river bridge was chosen for inspection and evaluation. SONAR and an optical camera were operated together to analyze the underwater image of the bridge. SONAR images were obtained by various methods to remove the environmental variables from the field experiment, and it was confirmed that the reliability of detecting damaged areas on piers was decreased when using SONAR alone. The SONAR equipment and the optical camera can be used simultaneously to overcome the limitations of SONAR in inspecting underwater structures.These results can be used as basic data for the development of similar technologies for underwater structure inspection.

• Smart Structures and Systems
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• v.31 no.4
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• pp.325-334
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• 2023

Computer vision-based damage detection enables non-contact, efficient and low-cost bridge health monitoring, which reduces the need for labor-intensive manual inspection or that for a large number of on-site sensing instruments. By leveraging recent semantic segmentation approaches, we can detect regions of critical structural components and identify damages at pixel level on images. However, existing methods perform poorly when detecting small and thin damages (e.g., cracks); the problem is exacerbated by imbalanced samples. To this end, we incorporate domain knowledge to introduce a hierarchical semantic segmentation framework that imposes a hierarchical semantic relationship between component categories and damage types. For instance, certain types of concrete cracks are only present on bridge columns, and therefore the noncolumn region may be masked out when detecting such damages. In this way, the damage detection model focuses on extracting features from relevant structural components and avoid those from irrelevant regions. We also utilize multi-scale augmentation to preserve contextual information of each image, without losing the ability to handle small and/or thin damages. In addition, our framework employs an importance sampling, where images with rare components are sampled more often, to address sample imbalance. We evaluated our framework on a public synthetic dataset that consists of 2,000 railway bridges. Our framework achieves a 0.836 mean intersection over union (IoU) for structural component segmentation and a 0.483 mean IoU for damage segmentation. Our results have in total 5% and 18% improvements for the structural component segmentation and damage segmentation tasks, respectively, compared to the best-performing baseline model.

• Journal of the Korean Society of Costume
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• v.54 no.6
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• pp.25-40
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• 2004

The rainbow has been considered as a perfect representative of color harmony in nature. In this study rainbow's colors include seven spectral colors and changeable colors according to observational angle. This study performed a bibliographical inquiry into rainbow colors and the survey research for classification of rainbow color images in fashion design. First, a bibliographical inquiry includes the definition of rainbow colors, physical formation principles of the rainbow, and its aesthetical attributes and symbolism. Second, this survey classifies rainbow color images in fashion design. The results of this study are as follows: 1. The rainbow was the religious and symbolic object before 17th century, and after that period, the rainbow became an aesthetical object. The main symbolic meanings are similar in eastern and western culture: temporary bridge between two world, divine nature, hope/beauty/richness, war/ death/flood/drought. 2. This survey shows that 6 main factors of rainbow color images in fashion design are 'vigorous', 'colorful'. 'fairy', 'fresh', 'mysterious', 'brilliant'. Rainbow color image in fashion design shows past and futuristic image at the same time. The purpose of this study is to systematized the images theoretical bases which are applied to color expression and of rainbow colors and to find out the development about rainbow theme by designers.

• Smart Structures and Systems
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• v.30 no.1
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• pp.17-34
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• 2022

For steel structures, fatigue cracks are critical damage induced by long-term cycle loading and distortion effects. Vision-based crack detection can be a solution to ensure structural integrity and performance by continuous monitoring and non-destructive assessment. A critical issue is to distinguish cracks from other features in captured images which possibly consist of complex backgrounds such as handwritings and marks, which were made to record crack patterns and lengths during periodic visual inspections. This study presents a parametric study on image-based crack identification for orthotropic steel bridge decks using captured images with complicated backgrounds. Firstly, a framework for vision-based crack segmentation using the atrous convolution-based Deeplapv3+ network (ACDN) is designed. Secondly, features on crack images are labeled to build three databanks by consideration of objects in the backgrounds. Thirdly, evaluation metrics computed from the trained ACDN models are utilized to evaluate the effects of obstacles on crack detection results. Finally, various training parameters, including image sizes, hyper-parameters, and the number of training images, are optimized for the ACDN model of crack detection. The result demonstrated that fatigue cracks could be identified by the trained ACDN models, and the accuracy of the crack-detection result was improved by optimizing the training parameters. It enables the applicability of the vision-based technique for early detecting tiny fatigue cracks in steel structures.