• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.238-242
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• 2007

Today's commercial high resolution satellite imagery such as that provided by IKONOS and QuickBird, offers the potential to extract useful spatial information for geographical database construction and GIS applications. Digital maps supply the most generally used GIS data probiding topography, road, and building information. Currently, the building information provided by digital maps is incompletely constructed for GIS applications due to planar position error and warped shape. We focus on extracting of the accurate building information including position, shape, and height to update the building information of the digital maps and GIS database. In this paper, we propose a new method of 3D building information extraction with a single high resolution satellite image and digital map. Co-registration between the QuickBird image and the 1:1,000 digital maps was carried out automatically using the RPC adjustment model and the building layer of the digital map was projected onto the image. The building roof boundaries were detected using the building layer from the digital map based on the satellite azimuth. The building shape could be modified using a snake algorithm. Then we measured the building height and traced the building bottom automatically using triangular vector structure (TVS) hypothesis. In order to evaluate the proposed method, we estimated accuracy of the extracted building information using LiDAR DSM.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.07a
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• pp.113-116
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• 2016

본 논문에서는 사람의 수작업을 통해서 작업을 하고 있는 도로 노면 문자 도색 작업을 자동화하기 위해 문자의 요소 인식과 인식한 결과로 문자 구성 정보를 전달하고, 이 정보를 이용하여 문자를 도색하는 프로그램을 구성하여 도로 노면 문자 도색 모의실험을 수행하였다. 정보처리기기에 프로그램을 구성하여 작업할 문자들을 입력 받아, 이미지 변환과 세선화와 역세선화를 거쳐 만들어진 영상에서 끝점, 2모음점, 3선 이상 모음점, 고립점 등 특징 점들을 추출하고 특징점들을 이용하여 글자를 인식하고, 특징점들을 이용하여 만든 정보를 도로 노면 문자 도색용 장비로 보낸다는 가정 하에 도색 프로그램을 수행 후, 나타난 결과를 피드백 하여 도색 프로그램을 수정하여 도로 노면 문자 도색 작업에 쓸 수 있는 성능의 결과를 구성하였다.

• International Journal of Automotive Technology
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• v.8 no.4
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• pp.513-520
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• 2007

In this paper, we propose an approach to identify the driving environment for intelligent highway vehicles by means of image processing and computer vision techniques. The proposed approach mainly consists of two consecutive computational steps. The first step is the lane marking detection, which is used to identify the location of the host vehicle and road geometry. In this step, related standard image processing techniques are adapted for lane-related information. In the second step, by using the output from the first step, a four-stage algorithm for vehicle detection is proposed to provide information on the relative position and speed between the host vehicle and each preceding vehicle. The proposed approach has been validated in several real-world scenarios. Herein, experimental results indicate low false alarm and low false dismissal and have demonstrated the robustness of the proposed detection approach.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2006.04a
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• pp.475-484
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• 2006

Recently, the studies on the extraction of 3-dimension coordinate and attribute information of objects using LiDAR data are carried out widely. LiDAR data has high locational accuracy, and advantage that can process data more fast because there's not coordinate transform when acquire of Data justly the ground coordinate by Acquiring. The purpose of the paper using only LiDAR data Manufacture road, building, contour That occupy a many parts of Digital Map. Estimated for possibility of Digital mapping using only LiDAR data As that compare accuracy with traditional Digital map.

• Journal of Korea Multimedia Society
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• v.3 no.5
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• pp.445-453
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• 2000

In this paper we propose the method which extracts lane using the grouped block snake algorithm. In the proposed algorithm, input image is divided into $8\times{8}$ blocks and then noise-included blocks are removed by a probability-based method. And also, we use hough transform to separate lane from the background image and suggest a grouped block snake method to detect road lane blocks. The proposed method reduces computational complexity and removes the noise in a more effective way compared to the pixel-based snake method.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.633-636
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• 2004

Airborne laser scanning thechnology has been studied in many applications, DSM(Digital Surface Model) development, building extraction, 3D virtual city modeling. In this paper, we will evaluate the possibility of airborne laser scanning technology for transportation application, especially for recognizing moving vehicles on road. First, we initially segment the region of roads from all LiDAR DATA using the GIS map and intensity image. Secondly, the segmented region is divided into the roads and vehicles using the height threshold value of local based window. Finally, the vehicles will be classified into the several types of vehicles by MDC(Minimum Distance Classification) method using the vehicle's geometry information, height, length, width, etc

• 한국지형공간정보학회:학술대회논문집
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• 2003.09a
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• pp.163-168
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• 2003

급속한 도시화와 교통 수요의 증가로 인해 각종 도로 정보가 빠르게 변화하고 있어 이에 대한 정보들의 추출, 수정 또는 보완의 중요성이 커지고 있다. 도로 정보 및 도로 파손 상태 정보를 이용하면 도로를 효율적이고 경제적으로 유자 관리할 수 있고, 수치지도 및 GIS 분석의 입력자료로서 사용될 수 있다. 본 연구에서는 분당지역의 항공사진을 이용하여 반자동으로 도로를 추출하였다. 항공사진에 탑햇 필터(top-hat filter)를 적용하고 적절한 임계값을 설정하여 후보 개체를 선택하고 모양 유사성을 고려하여 차로분리선만을 선택함으로써 효율적으로 차로분리선을 추출하였다. 추출된 차로분리선을 연결하고 중심선을 구함으로써 도심지역의 도로를 추출할 수 있었다.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.2 s.36
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• pp.33-42
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• 2006

Recently, the studies on the extraction of 3-dimension position information and attribute information of ground surface using LiDAR data. LiDAR data has high locational accuracy, and advantage that can process data more fast because there's not coordinate transform when acquire of Data justly the ground coordinate by Acquiring. The paper using only LiDAR data Manufacture road, building, contour That occupy a many parts of Digital Map. Estimated for possibility of Digital mapping using only LiDAR data As that compare accuracy with Digital map.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2004.03a
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• pp.551-557
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• 2004

미래의 텔레매틱스(telematics)환경에서 차량항법과 관련된 주요 핵심 기술은 동적 경로 안내 이외에 차량 자체의 지능화를 통해 운전자에게 주행 중인 도로에서 급경사, 급커브 구간에 대한 정보를 사전에 경고함으로써 사고를 방지하는 운전자 보조 및 경고 시스템(driver assistance and warning system) 구현으로 전망되고 있다. 이와 같은 기술이 구현되기 위해서는 현재 차량항법용 수치도로지도에서 도로의 단순 위치정보만으로는 불가능하며 도로의 곡선구간에서 평면 곡선반경과 같은 도로의 선형설계요소에 대한 정보가 필수적이다. 따라서 본 연구에서는 현재 전국적으로 구축되어있는 1/1000 수치지도의 도로중심선을 이용하여 실제 도로의 평면 선형설계요소를 자동으로 추출하기 위한 알고리즘을 개발하였고 이를 GUI 환경의 프로그램으로 구현함으로써 기존 도로의 정확한 평면 선형정보를 경제적이면서 효율적으로 획득할 수 있게 되었다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.71-73
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• 2019

How much and where vehicles exist is an essential element in the implementation of a GeoAI-based urban environment that reflects traffic information. In this paper, we trained vehicle data using Mask R-CNN that deep learning model useful for object detection and extraction, and verified vehicle detection in actual aerial images taken with drones.