• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.277-280
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• 2010

There is a need to convert the old low- or medium-resolution satellite image-based thematic mapping to the high-resolution satellite image-based mapping of GSD 1m grade or lower. There is also a need to generate middle- or large-scale thematic maps of 1:5,000 or lower. In this study, the DEM and orthoimage is generated with the KOMPSAT-2 stereo image of Yuseong-gu, Daejeon Metropolitan City. By utilizing the orthoimage, automatic extraction experiments of land cover information are generated for buildings, roads and urban areas, raw land(agricultural land), mountains and forests, hydrosphere, grassland, and shadow. The experiment results show that it is possible to classify, in detail, for natural features such as the hydrosphere, mountains and forests, grassland, shadow, and raw land. While artificial features such as roads, buildings, and urban areas can be easily classified with automatic extraction, there are difficulties on detailed classifications along the boundaries. Further research should be performed on the automation methods using the conventional thematic maps and all sorts of geo-spatial information and mapping techniques in order to classify thematic information in detail.

• Smart Media Journal
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• v.9 no.3
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• pp.107-115
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• 2020

Recently, BIM has become mandatory in the construction field, research on various use cases is increasing. In particular, when virtual reality technology, one of the core technologies of the 4th industrial revolution, and BIM are combined, it can be used in various fields such as preliminary design review and construction simulation. Until now, however, virtual reality grafting technology is only used as a simple prototype or as a model house. Also, it is difficult to activate virtual construction because it is expensive to produce high-quality virtual reality contents. Therefore, in this paper, in order to increase the utilization and quality of the virtual construction field, a study was conducted to shorten the material mapping time, which takes a lot of time when producing virtual reality contents using BIM. To this end, object properties were assigned to enable material mapping in the BIM model, and materials most used in the construction field were configured, and automated material function development and final tests were conducted that automatically map properties and materials. For the test, 10 models were used and the test was repeated three times, and the productivity improvement of about 50.16% was finally achieved. In the future, we plan to conduct research on physical data weight reduction based on the advanced material mapping automation function and the large-capacity BIM model.

• Korean Journal of Construction Engineering and Management
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• v.5 no.2 s.18
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• pp.90-105
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• 2004

Machines for crack sealing automation have been continually developed since the early 1990's because of the effectiveness of crack sealing that would be able to improve safety, quality and productivity. It has been considered challenging problem to detect crack network in pavement which includes noise (oil marks, skid marks, previously sealed cracks and inherent noise). Moreover, it is required to develop crack network mapping and modeling algorithm in order to accurately inject sealant along to the middle of cut crack network. The primary objective of this study is to propose machine vision algorithms (digital image processing algorithm and path planning algorithm) for fully automated pavement crack sealing. It is anticipated that the effective use of the proposed machine vision algorithms would be able to reduce error rate in image processing for detecting, mapping and modeling crack network as well as improving quality and productivity compared to existing vision algorithms.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.10
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• pp.833-838
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• 2016

This paper presents a performance evaluation of various feature-initialization algorithms for forward-viewing mono-camera based simultaneous localization and mapping (SLAM), specifically in indoor environments. For mono-camera based SLAM, the position of feature points cannot be known from a single view; therefore, it should be estimated from a feature initialization method using multiple viewpoint measurements. The accuracy of the feature initialization method directly affects the accuracy of the SLAM system. In this study, four different feature initialization algorithms are evaluated in simulations, including linear triangulation; depth parameterized, linear triangulation; weighted nearest point triangulation; and particle filter based depth estimation algorithms. In the simulation, the virtual feature positions are estimated when the virtual robot, containing a virtual forward-viewing mono-camera, moves forward. The results show that the linear triangulation method provides the best results in terms of feature-position estimation accuracy and computational speed.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.2
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• pp.128-137
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• 2011

The purpose of the FAPIS(Forest Aerial Photograph Interpretation System) development is to increase accuracy and efficiency of the digital forest cover type mapping for improving conventional analog-based mapping procedures by optimizing work-flow and mapping technology. The database models including digital forest cover type map, aerial photograph, and topographic map were designed for use in this system construction. The interface configured concisely to connect with functions such as search engine, display control, conversion to stereo interpretation mode, modification tools, automation of print layout and database models. It is expected that the standardization methodology based on this system can be applied and extended in making all kinds of digital thematic maps, providing decision-making and information of forest resources.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.10
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• pp.236-242
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• 2019

Recently, scanning projects have been carried out in various construction and construction fields for maintenance purposes. The point cloud generated by the scan results is composed of a number of points representing the object to be scanned. The process of extracting the necessary information, including dimensions, from such scan data is called paradox. The reverse engineering process of modeling a point cloud as BIM involves considerable manual work. Owing to the time-consuming reverse engineering nature of the work, the costs increase exponentially when rework requests are made, such as design changes. Reverse engineering automation technology can help improve these problems. On the other hand, the reverse design product is variable depending on the use, and the kind and detail level of the product may be different. This paper proposes the G2BM (Geometry-to-BIM mapping) rule definition method that automatically maps a BIM object from a primitive geometry to a BIM object. G2BM proposes a process definition and a customization method for reverse engineering BIM objects that consider the use case variability.

• Journal of the Korea Society of Computer and Information
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• v.29 no.11
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• pp.173-185
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• 2024

The U.S. federal government has established NIST SP 800-53 in response to the need for vulnerability management, and MITRE manages security vulnerabilities through CVE numbers. Although the relationship between NIST SP 800-53 and CVE is a crucial factor in vulnerability management, it is not clearly defined, making it challenging for security managers to identify control items that address the latest vulnerabilities. This study aims to analyze the relationship between NIST SP 800-53 and CVE to establish prioritization for evaluating security control items. Controls that are frequently associated with CVE should be prioritized for evaluation and improvement. The study derived the relevance between NIST SP 800-53 security controls through mapping CVE to STIG/SRG and used SecBERT, CyBERT, and RankT5 models to automate this mapping. The results confirmed the need to prioritize the improvement of specific security controls.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1085-1092
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• 2022

Travel distance is a parameter mainly used in the objective function of Construction Site Layout Planning (CSLP) automation models. To obtain travel distance, common approaches, such as linear distance, shortest-distance algorithm, visibility graph, and access road path, concentrate only on identifying the shortest path. However, humans do not necessarily follow one shortest path but can choose a safer and more comfortable path according to their situation within a reasonable range. Thus, paths generated by these approaches may be different from the actual paths of the workers, which may cause a decrease in the reliability of the optimized construction site layout. To solve this problem, this paper adopts reinforcement learning (RL) inspired by various concepts of cognitive science and behavioral psychology to generate a realistic path that mimics the decision-making and behavioral processes of wayfinding of workers on the construction site. To do so, in this paper, the collection of human wayfinding tendencies and the characteristics of the walking environment of construction sites are investigated and the importance of taking these into account in simulating the actual path of workers is emphasized. Furthermore, a simulation developed by mapping the identified tendencies to the reward design shows that the RL agent behaves like a real construction worker. Based on the research findings, some opportunities and challenges were proposed. This study contributes to simulating the potential path of workers based on deep RL, which can be utilized to calculate the travel distance of CSLP automation models, contributing to providing more reliable solutions.

• Journal of Mechanical Science and Technology
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• v.17 no.10
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• pp.1411-1422
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• 2003

The detection of free spaces between obstacles in a scene is a prerequisite for navigation of a mobile robot. Especially for stereo vision-based navigation, the problem of correspondence between two images is well known to be of crucial importance. This paper describes multi-range approach of area-based stereo matching for grid mapping and visual navigation in uncertain environment. Camera calibration parameters are optimized by evolutionary algorithm for successful stereo matching. To obtain reliable disparity information from both images, stereo images are to be decomposed into three pairs of images with different resolution based on measurement of disparities. The advantage of multi-range approach is that we can get more reliable disparity in each defined range because disparities from high resolution image are used for farther object a while disparities from low resolution images are used for close objects. The reliable disparity map is combined through post-processing for rejecting incorrect disparity information from each disparity map. The real distance from a disparity image is converted into an occupancy grid representation of a mobile robot. We have investigated the possibility of multi-range approach for the detection of obstacles and visual mapping through various experiments.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.77-89
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• 2022

In this paper, we propose a system which automatically generates SHACL schemas to describe and validate RDF knowledge graphs constructed by RML mappings. Unlike existing studies, the proposed system generates the schemas based on not only RML mapping rules but also metadata extracted from RML mapping input data in various formats such as CSV, JSON, XML or databases. Therefore, our schemas include the constraints on data type, string length, value range and cardinality, which were not present in the existing schemas. And we solves the problem with "repeated properties" which overlooked in existing studies. Through a conformance test consisting of 297 cases, we show that the proposed system generates correct constraints for the graphs. The proposed system can contribute to automation of the tedious and error-prone existing manual validation processes.