• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.4
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• pp.293-300
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• 2013

Road signs are important infrastructures for safe and smooth traffic by providing useful information to drivers. It is necessary to establish road sign DB for managing road signs systematically. To provide such DB, manually detection and recognition from imagery can be done. However, it is time and cost consuming. In this study, we proposed algorithms for automatic recognition of direction information in road sign image. Also we developed algorithm code using OpenCV library, and applied it to road sign image. To automatically detect and recognize direction information, we developed program which is composed of various modules such as image enhancement, image binarization, arrow region extraction, interesting point extraction, and template image matching. As a result, we can confirm the possibility of automatic recognition of direction information in road sign image.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.90-93
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• 2009

본 논문은 자동차 자동운행 시스템 연구 분야의 한 부분인 자동차 운행 중 도로상에 위치한 교통 신호등을 추적을 통해 검출하고, 인식하기 위한 방법과 관련된 연구이다. 교통 신호등은 색상 정보를 포함한 광원을 갖는 물체로서 표현되어지고 운전자에게 안전을 위해 준수해야 할 신호정보로써 제공되어 진다. 본 논문에서는 이러한 교통신호등의 인식을 위해 명도 분포도를 이용하여 관심영역을 필터링하고, 마스크와 HSI 색 공간영역에서의 색상과 채도, 밝기 정보를 이용한 유효값을 검출, 좌표변환, 보간법, YUV 모델을 이용한 그레이 영상으로의 변환, 닫힘 연산, 선명화 연산, 템플릿 매칭 방법을 적용함으로써 가로등과 같은 주변 환경이 갖는 색정보로부터 교통 신호등의 신호를 검출하고 인식하도록 하였다.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.3
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• pp.91-98
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• 2011

Road signs are part of the traffic facilities intended to guide drivers to their destinations in a safe and comfortable manner. Due to the creation of new routes, changes to the old routes, and the deterioration of road signs, road signs do require efforts to do ongoing field investigations and put the results in a database. The purpose of this study was to propose methodologies to do field investigations and build a database for road signs efficiently. For that purpose, a mobile mapping system was designed for field investigations. The designed mobile mapping system was comprised of three cameras to produce image information about road signs, GPS/IMU/DMI to obtain information about the position and attitude of a vehicle, and a laser scanner to generate information about the locations of road signs and routes. Also proposed in the study was a procedure to automatically detect the areas of road signs in the road signs images and recognize their characters.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.1318-1320
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• 2013

본 논문은, 도로표지 영상의 자동 획득, 관련 정보의 검출/인식 및 온라인 갱신 기능을 갖는 차세대 도로표지 관리시스템에 요구되는, 도로표지 영상으로부터 방향지시 정보과 국문지명을 검출하는 방법을 제안한다. 자획 폭 변환을 사용하여 비텍스트 정보를 구분하고, 한글 템플릿 매칭을 사용하여 국문 지명의 영역을 검출한다. 제안한 방법은 실제 도로표지 영상에 대해서 98%의 방향지시 정보 검출율과 92%의 국문지명 검출율 성능을 보였다.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.383-386
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• 2005

본 논문에서는 Hough 변환을 이용하여 도로 차선의 핵심 정보를 추출하고 차선을 인식하는 방법을 제안하고 실시간으로 차선 인식이 용이 하도록 차선 검출의 고속화 방법을 제안한다. 고속화를 위해 이미지를 작은 영역(Interest Zone)으로 분할하고 분할된 영역에 대해 Hough 변환을 수행하여 영역내의 차선을 검출한다. 검출된 차선의 패턴 정보를 이용하여 다음 Step의 Interest Zone을 결정하고 Hough 변환의 수행을 반복하여 차선 검출을 시도 하였다. 또한 실험 영상을 대상으로 시뮬레이션 수행한 결과를 제시하고 제안 방법의 유효성을 검증하였다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2005.11a
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• pp.195-198
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• 2005

본 논문에서는 Hough 변환을 이용하여 도로 차선의 핵심 정보를 추출하고 차선을 인식하는 방법을 제안하고 실시간으로 차선 인식이 용이 하도록 차선 검출의 고속화 방법을 제안한다. 고속화를 위해 이미지를 작은 영역(Interest Zone)으로 분할하고 분할된 영역에 대해 Hough 변환을 수행하여 영역내의 차선을 검출한다. 검출된 차선의 패턴 정보를 이용하여 다음 Step의 Interest Zone을 결정하고 Hough 변환의 수행을 반하여 차선 검출을 시도 하였다. 또한 실험 영상을 대상으로 시뮬레이션 수행한 결과를 제시하고 제안 방법의 유효성을 검증하였다.

• Spatial Information Research
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• v.2 no.2
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• pp.189-196
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• 1994

Adaptive smoothing filter is a filter that averages out the intensities around the pixels of similar intensities while conserving the discontinuties. When human eyes rec-ognize a map, the brain can easily assign one color for each element such as road or building while computer distinguishes all the minute color differences even for one ele¬ment. We can approach to the solution by using the adaptive smoothing filter so that the machine can assign one color for each element as much as we want, and it is found to be a very essential tool foor map segmentation of urban areas. The filter is applied to a scanned map, and it is used to extract roads and residential areas.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.8
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• pp.1693-1700
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• 2012

Recently, the warning system to aid drivers for safe driving is being developed. The system estimates the distance between the driver's car and the car before it and informs him of safety distance. In this paper, we designed and implemented the collision warning system which detects the car in front on the actual road situation and measures the distance between the cars in order to detect the risk situation for collision and inform the driver of the risk of collision. First of all, using the forward-looking camera, it extracts the interest area corresponding to the road and the cars from the image photographed from the road. From the interest area, it extracts the object of the car in front through the analysis on the critical value of the shadow of the car in front and then alerts the driver about the risk of collision by calculating the distance from the car in front. Based on the results of detecting driving cars and measuring the distance between cars, the collision warning system was designed and realized. According to the result of applying it in the actual road situation and testing it, it showed very high accuracy; thus, it has been verified that it can cope with safe driving.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.3 s.33
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• pp.87-94
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• 2005

3D positional information of lane can be automatically calculated tv combining GPS data, IMU data if coordinates of lane centers are given. The Road Safety Survey and Analysis Vehicle(RoSSAV) is currently under development to analyze three dimensional safety and stability of roads. RoSSAV has GPS and IMU sensors to get positional information of the vehicle and two road-facing CCD cameras for extraction of lane coordinates. In this paper, we develop technology that automatically detects centers of lanes from the road-facing cameras of RoSSAV. The proposed algorithm defines line-support regions by grouping pixels with similar edge orientation and magnitude together and extracts a line from each line support region by planar fitting. Then if extracted lines and the region in-between satisfy the criteria of brightness and width, we decide this region as lane. The proposed algorithm was more precise and stable than the previously proposed algorithm based on brightness threshold method. Experiments with real road scenes confirmed that lane was effectively extracted by the proposed algorithm.

• Proceedings of the Korea Multimedia Society Conference
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• 2004.05a
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• pp.243-246
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• 2004

본 논문은 영상인식 방법으로 개선된 Active Model을 이용한 방법을 제안한다. 제안된 방법은 모든 격자 블록 영역이 동일한 구조를 가지며, 기존의 Active net에서 문제가 되었던 목표물을 탐지하는 능력이 개선되었다. 실험 결과로서 제안된 방법이 수직, 수평 방향에서 목표물 포착에 효과적임을 보여주었으며, 실제 도로 영상에 적용한 결과 제안한 방법의 효율성을 입증할 수 있었다.