• 반도체디스플레이기술학회지
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• 제21권1호
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• pp.22-26
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• 2022

This paper proposes a new method for the recognition of road surface marks and numbers. The proposed method designates a region of interest on the road surface without first detecting a lane. The road surface markings are extracted by location and size using a connection component analysis. Distortion due to the perspective effect is minimized by normalizing the size of the road markings. The road surface marking of the connected component is recognized by matching it with the stored road marking templates. The proposed method is implemented using C language in Raspberry Pi 4 system with a camera module for a real-time image processing. The system was fixedly installed in a moving vehicle, and it recorded a video like a vehicle black box. Each frame of the recorded video was extracted, and then the proposed method was tested. The results show that the proposed method is successful for the recognition of road surface marks and numbers.

• 한국자동차공학회논문집
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• 제22권7호
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• pp.107-116
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• 2014

This paper presents camera-based road surface marking detection methods suited to sensor fusion-based positioning system that consists of low-cost GPS (Global Positioning System), INS (Inertial Navigation System), EDM (Extended Digital Map), and vision system. The proposed vision system consists of two parts: lane marking detection and RSM (Road Surface Marking) detection. The lane marking detection provides ROIs (Region of Interest) that are highly likely to contain RSM. The RSM detection generates candidates in the regions and classifies their types. The proposed system focuses on detecting RSM without false detections and performing real time operation. In order to ensure real time operation, the gating varies for lane marking detection and changes detection methods according to the FSM (Finite State Machine) about the driving situation. Also, a single template matching is used to extract features for both lane marking detection and RSM detection, and it is efficiently implemented by horizontal integral image. Further, multiple step verification is performed to minimize false detections.

• 방송공학회논문지
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• 제21권1호
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• pp.87-96
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• 2016

최근 웹 또는 모바일 기기에서 전자지도를 이용한 정보 제공 서비스의 활성화로 도로 노면의 다양한 기호들을 자동으로 인식하는 기술이 요구되고 있다. 본 논문에서는 HOG-SP(Histogram of oriented Gradients-Split Projection) 서술자를 이용하여 도로 노면에 표시된 11가지의 방향지시기호를 자동으로 인식하는 방법을 제안하였으며, 인식된 방향지시기호를 기반으로 차선 위치 검출의 성능 향상을 나타내었다. 네이버 로드 뷰 영상으로 실험하여 제안하는 방법으로 81.99%의 인식률을 보였으며, 기존의 다른 특징들과의 비교 실험을 통해 제안하는 방법의 우수성을 입증하였다. 또한, 방향지시기호를 먼저 인식한 후 차선의 위치를 검출함으로써 단순히 차선의 위치만 검출하는 방법보다 7.64% 더 높은 검출률을 얻었다.

• 제어로봇시스템학회논문지
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• 제22권12호
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• pp.1053-1060
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• 2016

As location recognition for autonomous vehicles develops, the need for a precise map for autonomous driving has increased. A precise map must be built based upon accurate position. Recent studies have accelerated research in this area by using various sensors that calculate the accurate position by comparing and recognizing objects around the roads. However, application of such methods is limited because these studies only take objects with significant verticality into consideration. Thus, new research is needed to overcome the limitations: a method that is not constrained by the existence of certain types of surrounding objects shall be proposed. Most roads contain road marking information, such as lanes, direction signs, and pedestrian crossings. Such information on the road surface is a valuable resource for building a precise map. This paper proposes a method of building a precise map by using road marking information.