• Title/Summary/Keyword: 전자지도

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Novel VO and HO Map for Vertical Obstacle Detection in Driving Environment (새로운 VO, HO 지도를 이용한 차량 주행환경의 수직 장애물 추출)

  • Baek, Seung-Hae;Park, Soon-Yong
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.2
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    • pp.163-173
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    • 2013
  • We present a new computer vision technique which can detect unexpected or static vertical objects in road driving environment. We first obtain temporal and spatial difference images in each frame of a stereo video sequence. Using the difference images, we then generate VO and HO maps by improving the conventional V and H disparity maps. From the VO and HO maps, candidate areas of vertical obstacles on the road are detected. Finally, the candidate areas are merged and refined to detect vertical obstacles.

Extraction Of Dashed Line Information On Maps Using Visual Mechanism (시각매카니즘을 이용한 지도에서의 파선정보추출기구의 제안)

  • Park, Si-Dong;Kim, Wook-Hyun
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.1
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    • pp.170-177
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    • 1996
  • In this paper, we propose a neural network for extracting dashed lines from map images based on the feature extracting path be found in a cat and monkey's visual cortex. The proposed system converts a color image to a binary image and extracts the lines per orientation. Next, the system removes the lines longer than the dashed line and extracts the dashed lines by finding the consecutive short lines. The proposed system for extracting the dashed lines was tested using 1/25,000 scaled maps published by the National Geographic Institute of Korea. This paper shows that the proposed system can extract the dashed-lines from maps.

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Depth Map Correction Algorithm based on Segmentation in Multi-view Systems (다중시점 환경에서의 슈퍼픽셀 세그먼테이션 기반 깊이 영상 개선 알고리즘)

  • Jung, Woo-Kyung;Han, Jong-Ki
    • Journal of Broadcast Engineering
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    • v.25 no.6
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    • pp.954-964
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    • 2020
  • In immersive media, the most important factor that provides immersion is depth information. Therefore, it is essential to obtain high quality depth information in order to produce high quality immersive media. In this paper we propose an algorithm to improve depth map, considering the segmentation of images and the relationship between multiple views in multi-view systems. The proposed algorithm uses a super-pixel segmentation technique to divide the depth map of the reference view into several segments, and project each segment into adjacent view. Subsequently, the depth map of the adjacent view is improved using plane estimation using the information of the projected segment, and then reversed to the reference view. This process is repeated for several adjacent views to improve the reference depth map by updating the values of the improved adjacent views and the initial depth map of the reference view. Through simulation, the proposed algorithm is shown to surpass the conventional algorithm subjectively and objectively.

A Study on Updated Object Detection and Extraction of Underground Information (지하정보 변화객체 탐지 및 추출 연구)

  • Kim, Kwangsoo;Lee, Heyung-Sub;Kim, Juwan
    • Journal of Software Assessment and Valuation
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    • v.16 no.2
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    • pp.99-107
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    • 2020
  • An underground integrated map is being built for underground safety management and is being updated periodically. The map update proceeds with the procedure of deleting all previously stored objects and saving newly entered objects. However, even unchanged objects are repeatedly stored, deleted, and stored. That causes the delay of the update time. In this study, in order to shorten the update time of the integrated map, an updated object and an unupdated object are separated, and only updated objects are reflected in the underground integrated map, and a system implementing this technology is described. For the updated object, an object comparison method using the center point of the object is used, and a quad tree is used to improve the search speed. The types of updated objects are classified into addition and deletion using the shape of the object, and change using its attributes. The proposed system consists of update object detection, extraction, conversion, storage, and history management modules. This system has the advantage of being able to update the integrated map about four times faster than the existing method based on the data used in the experiment, and has the advantage that it can be applied to both ground and underground facilities.

A Study on the 4D Traffic Condition Board based on a Mash-up Technology (Mash-up 기술을 이용한 4D Wall-Map 구성체계)

  • Kim, Joo-Hwan;Yang, Seung-Mook;Nam, Doo-Hee
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.8 no.3
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    • pp.27-33
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    • 2009
  • Content used in mashups is typically obtained from a third party source through a public interface or API (web services). Other methods of obtaining content for mashups include Web feeds (e.g. RSS or Atom), and screen scraping. A mashup or meshup Web application has two parts: A new service delivered through a Web page, using its own data and data from other sources. The blended data, made available across the Web through an API or other protocols such as HlTP, RSS, REST, etc. There are many types of mashups, such as consumer mashups, data mashups, and Business Mashups. The most common mashup is the consumer mashup, which are aimed at the general public. Examples include Google Maps, iGuide, and RadioClouds. 4D Wall-map display is data mashups combine similar types of media and information from multiple sources into a single representation. This technology focus data into a single presentation and allow for collaborative action among ITS-related information sources.

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Efficient Self-supervised Learning Techniques for Lightweight Depth Completion (경량 깊이완성기술을 위한 효율적인 자기지도학습 기법 연구)

  • Park, Jae-Hyuck;Min, Kyoung-Wook;Choi, Jeong Dan
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.20 no.6
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    • pp.313-330
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    • 2021
  • In an autonomous driving system equipped with a camera and lidar, depth completion techniques enable dense depth estimation. In particular, using self-supervised learning it is possible to train the depth completion network even without ground truth. In actual autonomous driving, such depth completion should have very short latency as it is the input of other algorithms. So, rather than complicate the network structure to increase the accuracy like previous studies, this paper focuses on network latency. We design a U-Net type network with RegNet encoders optimized for GPU computation. Instead, this paper presents several techniques that can increase accuracy during the process of self-supervised learning. The proposed techniques increase the robustness to unreliable lidar inputs. Also, they improve the depth quality for edge and sky regions based on the semantic information extracted in advance. Our experiments confirm that our model is very lightweight (2.42 ms at 1280x480) but resistant to noise and has qualities close to the latest studies.

Application Study on Real-time X-band Radar based on GIS Web-site (GIS 웹사이트 기반 실시간 X-band 레이더 응용연구)

  • Youngjun Yang;Yukyung Lee
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2022.11a
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    • pp.321-322
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    • 2022
  • In this study, the marine environment is measured and analyzed in real time through the X-band radar installed on the rooftop of the Sokcho Beach administrative Welfare Center and Ulleungdo. Afterwards, the goal is to transmit the analysis results to the client PC. Using electronic maps and electronic navigational charts, the measurement results are overlaid on GIS (spatial information system), real-time data are shared through a website, and information is displayed through a web server. Currently, CCTV information and marine environment information are displayed on the website, but various application studies such as the use of Open AP I will be conducted in the future.

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Rotation-robust text localization technique using deep learning (딥러닝 기반의 회전에 강인한 텍스트 검출 기법)

  • Choi, In-Kyu;Kim, Jewoo;Song, Hyok;Yoo, Jisang
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2019.06a
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    • pp.80-81
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    • 2019
  • 본 논문에서는 자연스러운 장면 영상에서 임의의 방향성을 가진 텍스트를 검출하기 위한 기법을 제안한다. 텍스트 검출을 위한 기본적인 프레임 워크는 Faster R-CNN[1]을 기반으로 한다. 먼저 RPN(Region Proposal Network)을 통해 다른 방향성을 가진 텍스트를 포함하는 bounding box를 생성한다. 이어서 RPN에서 생성한 각각의 bounding box에 대해 세 가지의 서로 다른 크기로 pooling된 특징지도를 추출하고 병합한다. 병합한 특징지도에서 텍스트와 텍스트가 아닌 대상에 대한 score, 정렬된 bounding box 좌표, 기울어진 bounding box 좌표를 모두 예측한다. 마지막으로 NMS(Non-Maximum Suppression)을 이용하여 검출 결과를 획득한다. COCO Text 2017 dataset[2]을 이용하여 학습 및 테스트를 진행하였으며 주관적으로 평가한 결과 기울어진 텍스트에 적합하게 회전된 영역을 얻을 수 있음을 확인하였다.

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Design and Application of AMR Using SLAM and ROS (SLAM과 ROS를 활용한 AMR 설계 및 응용)

  • Cho, Su-Je;Choi, Seoung-Yeol;An, Jae-Yong;Hong, Sung-Su;Choi, Hong-Yong
    • Proceedings of the Korea Information Processing Society Conference
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    • 2021.11a
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    • pp.1372-1375
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    • 2021
  • 최근 산업 현장에서 많은 안전사고가 일어나고 있고, 현장 노동력의 부족으로 무인 로봇 시스템들을 도입하는 등 다양한 변화를 맞이하고 있다. 이에 차세대 자동화 시스템은 보다 유연하고 지능적이어야 한다. AGV(Automatic Guided Vehicle)의 경우 실시간으로 변하는 현장에 대응하기 어렵고, 새로운 어플리케이션에 대한 제품개발의 어려움이 따른다. 이에 대한 대안으로 AGV 인식 스택을 재구축하여 인간과 동일한 공간인식 능력을 갖춘 AMR(Autonomous Mobile Robot)이 대두되고 있다. 본 연구에서는 SLAM과 ROS를 이용하여 AMR의 기능을 구축하였다. YD Lidar 센서와 SLAM을 이용하여 주변 환경을 지도화 하여 로봇의 현재 위치를 파악할 수 있도록 제작하였고, 직접 지도상의 최적 경로를 파악하여 주변 장애물을 회피하며 주행할 수 있음을 확인하였다. DC 모터의 응답 특성에 따라 주행 속도, 조향각 등을 제어할 수 있도록 구현하였다.

전자머니 서비스 종류와 내용-유럽은 IC카드형, 미국은 네트워킹형

  • Korean Associaton of Information & Telecommunication
    • 정보화사회
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    • s.105
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    • pp.15-17
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    • 1996
  • 세계적으로 전자머니의 실험과 실용화는 하루가 다르게 변화를 보이고 있을정도로 움직임이 매우 빠르다. 여러 전자머니중에서 현재 IC카드형 전자머니의 실험사례가 많은 편이다. 이는 전자머니를 둘러싼 국제 신용카드업계의 움직임과 관련이 깊다. 신용카드 진영뿐만 아니라 은행들도 현금카드를 IC카드화하여 그 ID번호를 써서 네트워크상 결제를 할 수 있는 가능성을 현실화해가고 있다. 따라서 전자머니의 업계지도는 아직은 크게 유동적이다. 현재 움직임이 구체화된 대표적인 전자머니의 서비스와 명칭과 기능을 대략적으로 알아본다.

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