• Journal of the KSME
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• v.25 no.2
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• pp.122-129
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• 1985

진동신호 측정 및 해석과 병행하여 구조 해석용 컴퓨터 소프트웨어의 활용은 결함 진단 기술을 더욱 다양하게 할 수 있으며 궁국에 가서는 컴퓨터 시뮬페이션에 의하여 결함 여부 및 위치색 출을 더욱 효과적으로 수행할 수 있다. 물론 이를 위하여는 컴퓨터 모델링 기술의 개발, 시스템 Indentification 문제, 시스템의 선형화 문제, 경계조건의 변화를 모델링하는 문제등 제반 문제점이 선결되어져야 한다. 진동신호 측정 및 분석에 의한 결함탐지 및 컴퓨터 소프트웨어 활용에 관한 상호관계를 도표로 표시하면 그림 1과 같다.

• Journal of the Korea Computer Graphics Society
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• v.8 no.2
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• pp.15-22
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• 2002

Image segmentation methods partition an image into meaningful regions. For image composition and analysis, it is desirable for the partitioned regions to represent meaningful objects in terms of human perception and manipulation. Despite the recent progress in image understanding, however, most of the segmentation methods mainly employ low-level image features and it is still highly challenging to automatically segment an image based on high-level meaning suitable for human interpretation. The concept of HCI (Human Computer Interaction) can be applied to operator-assisted image segmentation in a manner that a human operator provides guidance to automatic image processing by interactively supplying critical information about object boundaries. Intelligent Scissors and Snakes have demonstrated the effectiveness of human-assisted segmentation [2] [1]. This paper presents a method for interactive image segmentation for more efficient and effective detection and tracking of object boundaries. The presented method is partly based on the concept of Intelligent Scissors, but employs the well-established Canny edge detector for stable edge detection. It also uses "sewing method" for including weak edges in object boundaries, and 5-direction search to promote more efficient and stable linking of neighboring edges than the previous methods.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.1
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• pp.87-98
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• 2012

A river boundary is defined as the intersection between a main stream of a river and the land. Mapping of the river boundary is important for the protection of the properties in river areas, the prevention of flooding and the monitoring of the topographic changes in river areas. However, the utilization of the ground surveying technologies is not efficient for the mapping of the river boundary due to the irregular surfaces of river zones and the dynamic changes of water level of a river stream. Recently, the spatial information data sets such as the airborne LiDAR and aerial images are widely used for coastal mapping due to the acquisition of the topographic information without human accessibility. Due to these advantages, this research proposes a semi-automatic method for mapping of the river boundary using the spatial information data set such as the airborne LiDAR and the aerial photographs. Multiple image processing technologies such as the image segmentation algorithm and the edge detection algorithm are applied for the generation of the 3D river boundary using the aerial photographs and airborne topographic LiDAR data. Check points determined by the experienced expert are used for the measurement of the horizontal and vertical accuracy of the generated 3D river boundary. Statistical results show that the generated river boundary has a high accuracy in horizontal and vertical direction.

• Spatial Information Research
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• v.18 no.3
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• pp.23-32
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• 2010

LIDAR data are useful for forest applications such as bare-earth DEM generation for forest areas, and estimation of tree height and forest biomass. As a core preprocessing procedure for most forest applications, this study attempts to develop an efficient method to detect forest areas from LIDAR data. First, we suggest three perceptual cues based on multiple return characteristics, height deviation and spatial distribution, being expected as reliable perceptual cues for forest area detection from LIDAR data. We then classify the potential forest areas based on the individual cue and refine them with a bi-morphological process to eliminate falsely detected areas and smoothing the boundaries. The final refined forest areas have been compared with the reference data manually generated with an aerial image. All the methods based on three types of cues show the accuracy of more than 90%. Particularly, the method based on multiple returns is slightly better than other two cues in terms of the simplicity and accuracy. Also, it is shown that the combination of the individual results from each cue can enhance the classification accuracy.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.22 no.1
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• pp.89-103
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• 2009

This study investigates the applicability of the time reversal concept in modem acoustics to the Lamb waves, which have been widely studied for defect detection in plate-like structures. According to conventional time reversal acoustics, an input signal can be reconstructed at an excitation point if an output signal recorded at another point is reversed in the time domain and emitted back to the original source point. However, the application of a time reversal process(TRP) to Lamb wave propagations is complicated due to velocity and amplitude dispersion characteristics of Lamb waves and reflections from the boundaries of a structure. In this study, theoretical investigations are presented to better understand the time reversibility of Lamb waves. In particular, the effects of within-mode dispersion, multimode dispersion, amplitude dispersion, and reflections from boundaries on the TRP are theoretically formulated. Simple numerical case studies are conducted to validate the theoretical findings of this study.

• Spatial Information Research
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• v.3 no.2
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• pp.91-102
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• 1995

The purposes of this paper are to find ways to detect ecotone between two eco'||'&'||'not;systems, measure the width and size of ecotone around the Mt. Pukhansan National Park, and investigate environmental impacts, if any, on the forest ecosystem of the park by human activities. Normalized Difference Vegetation Index(NDVI) derived from TM data and the ana'||'&'||'not;lytical capabilities of GIS are used to investigate characteristics of the ecotone, or the impact zone, of the park. Major findings of the study can be summarized as follows: First, it was found that ecotone of the park could be identified from NDVI -distance curves deri"ed by a series of buffering op'||'&'||'not;erations. Second, NDVIs of all three years of the national park are about 14 percent higher than surrounding areas. Third, width of ecotone were found to be closely related to phenology, adjacent land use, environmental degradation, etc. Third, ecotone of the study area was nearly douvled during 1985-1993 period, which might be caused by heavy trampling of visitors. Thus it can be concluded that further studies are needed to find exact causes of the deterioration of plant communities of the ecotone of the park.

• Journal of the Korean Geographical Society
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• v.45 no.4
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• pp.502-520
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• 2010

The main objective of the paper is to develop a GIS-based method for delineating spatial clusters. Major tasks are: (i) to devise a sustainable algorithm with reference to various methods developed in the fields of geographic boundary analysis and cluster detection; (ii) to develop a GIS-based program to implement the algorithm. The main results are as follows. First, it is recognized that the AMOEBA technique utilizing LISA is the best candidate. Second, a modified version of the AMOEBA technique is proposed and implemented in a GIS environment. Third, the validity and usefulness of the modified AMOEBA algorithm is assured by its applications to test and real data sets.

• Journal of the Korea Society for Simulation
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• v.31 no.2
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• pp.11-20
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• 2022

There is a critical need for AI assistance in guard operations of Army base perimeters, which is exacerbated by changes in the national defense and security environment such as force reduction. In addition, the possibility for human error inherent to perimeter guard operations attests to the need for an innovative revamp of current systems. The purpose of this study is to propose a real-time object detection AI tailored to military CCTV surveillance with three unique characteristics. First, training data suitable for situations in which relatively small objects must be recognized is used due to the characteristics of military CCTV. Second, we utilize a data augmentation algorithm suited for military context applied in the data preparation step. Third, a noise reduction algorithm is applied to account for military-specific situations, such as camouflaged targets and unfavorable weather conditions. The proposed system has been field-tested in a real-world setting, and its performance has been verified.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.625-628
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• 2019

양돈 업계에서 돼지의 무게는 생산성 측면에서 매우 중요한 요인 중 하나이다. 탑뷰 카메라를 통해 획득된 이미지에서 돼지의 무게를 추정할 때 오차가 적고 신뢰도 있는 결과를 보이기 위해, 오차의 주요 원인인 돼지의 머리를 제거하여야 한다. 우선, 돼지의 머리를 제거하기 위해서는 귀를 탐지하여야 한다. 그러나 돼지의 자세가 바르지 못한 경우 겹침으로 인해 돼지의 귀와 머리가 구분되지 않는 경우가 발생하고, 귀 탐지 과정에서 고려해야 할 변수가 많아지므로 연산량과 수행 시간이 증가한다. 따라서 돼지의 무게 추정을 위해서 돼지의 머리를 제거할 때 돼지의 자세 판정은 필수적이다. 본 논문에서는 돼지의 중점으로부터 돼지의 경계선을 연결한 선분의 길이를 비교하여 돼지의 자세를 빠르게 결정하였다. 이를 통해 자세가 바른 돼지의 머리를 제거하여 돼지의 무게를 측정하는 방법을 제안한다. 실험 결과, 7.8 ms의 수행 시간과 0.97 이상의 정확도로 돼지머리 제거를 위한 자세를 결정할 수 있음을 확인하였다.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.4
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• pp.45-53
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• 2013

Global warming causes sea levels to rise and global changes apparently taking place including coastline changes. Coastline change due to sea level rise is also one of the most significant phenomena affected by global climate change. Accordingly, Coastline change detection can be utilized as an indicator of representing global climate change. Generally, Coastline change has happened mainly because of not only sea level rise but also artificial factor that is reclaimed land development by mud flat reclamation. However, Arctic coastal areas have been experienced serious change mostly due to sea level rise rather than other factors. The purposes of this study are automatic extraction of coastline and identifying change. In this study, in order to extract coastline automatically, contrast of the water and the land was maximized utilizing modified NDWI(Normalized Difference Water Index) and it made automatic extraction of coastline possibile. The imagery converted into modified NDWI were applied image processing techniques in order that appropriate threshold value can be found automatically to separate the water and land. Then the coastline was extracted through edge detection algorithm and changes were detected using extracted coastlines. Without the help of other data, automatic extraction of coastlines using LANDSAT was possible and similarity was found by comparing NLCD data as a reference data. Also, the results of the study area that is permafrost always frozen below $0^{\circ}C$ showed quantitative changes of the coastline and verified that the change was accelerated.