• Proceedings of the KIEE Conference
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• summer
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• pp.1196-1198
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• 2004

This paper represents the improvement of floating point operation for AC servo motor controller based on fixed point operation DSP. TMS320F2812 has fixed point operation processing structure. The controller parameters are modified to the digitized data by scaling the original parameters. TMS320F 2812 is a 32-bit processor, and it could have enough accuracy to got the digitized data this procedure is implemented and the experiments controling a AC servo system.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.1
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• pp.43-52
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• 2009

LIDAR data, as the source of the 3D information of buildings, are used many modeling fields such as three-dimensional city models in urban planning and the visibility analysis of buildings. This study suggests a methodology, that is characterized by combining image-based and point-based process, for minimizing the user's intervention and automatically extracting building boundary only using the LIDAR data. Image processing methodology is firstly used to separate building and non-building regions from LIDAR data. Moreover, building regions are then classified main roof into remaining parts by the statistical analysis of height values, and the remaining parts are processed separately. Through the experimental results of study areas which exist many types of buildings, for example, apartment-type, stair-type, complex-type, etc. Approximately 90% building boundaries are automatically extracted by the proposed methodology.

• Proceedings of the Korea Contents Association Conference
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• 2005.11a
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• pp.200-204
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• 2005

POS system that become that is supply net administration and computerization fetters of customer management that become point in distribution network constructed database and use XML-Encryption that is certificate techniques of PKI and standard of security for security that is XML's shortcoming and design distributed processing POS system using XML for data integration by introduction of Ubiquitous concept. This POS system has four advantages. First, high portability Second, efficiency of data transmission. Third, improvement of data process speed. Fourth, security of data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.6
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• pp.628-633
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• 2018

The accuracy of GNSS depends on several factors from the equipment used in data processing because GNSS positioning can be used differently depending on the accuracy required. In the case of the control point surveying requiring high accuracy, GNSS surveying is performed using the relative positioning method, and the observation time and data processing s/w are used differently depending on the class of the control points. On the other hand, the accuracy of academic software depends on the skill of the user, so it may be better to use commercial software in the case of a short baseline. In this study, the results of GNSS survey data were compared using scientific software and commercial software. The results showed that the horizontal position showed a difference of less than 2 cm and the height showed a difference of less than 5 cm. These differences were found to be in the error ranges specified in the unified control point survey regulations. Based on the above results, the commercial s/w can be used for GNSS data processing at the midterm baseline rather than the long baseline.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.6_3
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• pp.1325-1332
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• 2023

Recently, much research is being conducted based on point cloud data for the growth of innovations such as construction automation in the transportation field and virtual national space. This data is often measured through remote control in terrain that is difficult for humans to access using devices such as UAVs and UGVs. Drones, one of the UAVs, are mainly used to acquire point cloud data, but photogrammetry using a vision camera, which takes a lot of time to create a point cloud map, is difficult to apply in construction sites where the terrain changes periodically and surveying is difficult. In this paper, we developed a point cloud mapping system by adopting non-repetitive scanning LiDAR and attempted to confirm improvements through field application. For accuracy analysis, a point cloud map was created through a 2 minute 40 second flight and about 30 seconds of software post-processing on a terrain measuring 144.5 × 138.8 m. As a result of comparing the actual measured distance for structures with an average of 4 m, an average error of 4.3 cm was recorded, confirming that the performance was within the error range applicable to the field.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.6
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• pp.72-79
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• 1998

In this paper, image processing algorithm is studied to enhance the preciseness of the geometry while converting captured images to CAD data. A program is developed as a result. The code, in the image processing, utilizes outline trace, point data smoothing algorithm. It is capable of automatically generating design data by converting input image data to the CAD data. The output can be made in DXF, IGES formats. The current research can be utilized as a base data for the development of factory automation or flexible manufacturing system which adopt image processing based automatic inspection and measuring system.

• Journal of the Society of Naval Architects of Korea
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• v.58 no.5
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• pp.303-313
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• 2021

Recently, quality control of the Liquefied Natural Gas Carrier (LNGC) cargo hold and block-erection interference areas using 3D scanners have been performed, focusing on large shipyards and the international association of classification societies. In this study, as a part of the research on LNGC cargo hold quality management advancement, a study on deep-learning-based scaffolding system 3D point cloud object detection and post-processing were conducted using a LNGC cargo hold 3D point cloud. The scaffolding system point cloud object detection is based on the PointNet deep learning architecture that detects objects using point clouds, achieving 70% prediction accuracy. In addition, the possibility of improving the accuracy of object detection through parameter adjustment is confirmed, and the standard of Intersection over Union (IoU), an index for determining whether the object is the same, is achieved. To avoid the manual post-processing work, the object detection architecture allows automatic task performance and can achieve stable prediction accuracy through supplementation and improvement of learning data. In the future, an improved study will be conducted on not only the flat surface of the LNGC cargo hold but also complex systems such as curved surfaces, and the results are expected to be applicable in process progress automation rate monitoring and ship quality control.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.209-212
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• 2006

This paper presents design and implementation methods of the eye-controlled mouse using the real-time tracking of the three dimensional gazing point. The proposed method is based on three dimensional data processing of eye images in the 3D world coordinates. The system hardware consists of two conventional CCD cameras for acquisition of stereoscopic image and computer for processing. And in this paper, the advantages of the proposed algorithm and test results are described.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.431-434
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• 2019

In the case of blur processing, it is common to use a tool such as Photoshop to perform processing manually. However, it can be considered very efficient if the blur is processed at one time in the object detection process. Based on this point, we can use the object detection model to blur the objects during the process. The object detection is performed by using the YOLO [3] model. If such blur processing is used, it may be additionally applied to streaming data of video or image.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.733-734
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• 2016

This study proposes a novel approach for ground segmentation of 3D point cloud. We combine two techniques: gradient threshold segmentation, and mean height evaluation. Acquired 3D point cloud is represented as a graph data structures by exploiting the structure of 2D reference image. The ground parts nearing the position of the sensor are segmented based on gradient threshold technique. For sparse regions, we separate the ground and nonground by using a technique called mean height evaluation. The main contribution of this study is a new ground segmentation algorithm which works well with 3D point clouds from various environments. The processing time is acceptable and it allows the algorithm running in real time.