• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1408-1410
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• 2015

Information about the painted road markings and other painted road objects play an important part in keeping safety of drivers. Some researchers have presented research approaches and dealt with road markings detection. In this paper, we present comprehensive survey of these techniques, and review some of them like a machine learning method, template matching method for road markings detection and classification, method of detection and classification of road markings using curve-based prototype fitting, signed edge signature method.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.226-231
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• 1998

This paper describes how a priori road geometry and its estimation may be used to detect road boundaries and lane markings in road scene images. We assume flat road and road boundaries and lane markings are all Bertrand curves which have common principal normal vectors. An active contour is used for the detection of road boundary, and we reconstruct its geometric property and make use of it to detect lane markings. Our approach to detect road boundary is based on minimizing energy function including edge related term and geometric constraint term. Lane position is estimated by pixel intensity statistics along the parallel curve shifted properly from boundary of the road. We will show the validity of our algorithm by processing real road images.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.1
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• pp.62-68
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• 2012

In this paper, a detection method of a pedestrian safety road marking was proposed. The proposed algorithm uses laser range and reflectivity of a range finder (LRF). For a detection of crosswalk marking and stop line, the DFT (Discrete Fourier Transform) of reflectivity and cross-correlation method between the reference replica and the measured reflectivity are used. A speed bump is detected through measuring an altitude difference of two LRFs which have the different tilted angle. Furthermore, we proposed a velocity constrained a detection method of a speed bump. Finally, the proposed methods are tested in on-line, on the pavement of a road. The considered road markings are wholly detected. The localization errors of both road markings are smaller than 0.4 meter.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.161-164
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• 1999

An effective approach to lane detection in driver assistance system (DAS) is proposed, based on the decomposition of lane markings. The properties of the decomposed lane markings are discussed, and analyses on lane curvature are given. The current lane on road is detected quickly, the neighboring lane regions are also extracted for lane planning of the vehicle, and the parameters of lane structure are accurately estimated.

• Journal of Broadcast Engineering
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• v.21 no.1
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• pp.87-96
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• 2016

Recently, there is a need for automatic recognition of a variety of symbols on roads because of activation of information services using digital maps on the Web or mobile devices. This paper proposes a method which automatically recognizes 11 kinds of symbolic road markings on the road surface with HOG-SP(Histogram of oriented Gradients-Split Projection) descriptor and shows improvement of lane position detection with recognized symbolic road markings. With the proposed method, recognition rate of 81.99% has been proven on NAVER road view images and the experiments proves the superiority of proposed method by comparisons with other existing methods. Moreover, this paper shows 7.64% higher lane position detection rate by recognizing road surface marking beforehand than only detecting lanes' positions.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.8
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• pp.773-780
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• 2015

Navigation in outdoor environments is a fundamental and challenging problem for unmanned ground vehicles. Detecting lane markings or boundaries on the road may be one of the solutions to make navigation easy. However, because of various environments and road conditions, a robust lane detection is difficult. In this paper, we propose a new approach for estimating virtual lanes on a traversable region. Estimating the virtual lanes consist of two steps: (i) we detect virtual road region through road model selection based on traversability at current frame and similarity between the interframe and (ii) we estimate virtual lane using the number of lane on the road and results of previous frame. To improve the detection performance and reduce the searching region of interests, we use a probability map representing the traversability of the outdoor terrain. In addition, by considering both current and previous frame simultaneously, the proposed method estimate more stable virtual lanes. We evaluate the performance of the proposed approach using real data in outdoor environments.

• International Journal of Highway Engineering
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• v.14 no.1
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• pp.9-16
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• 2012

The performance of road markings is classified into the visibility at daytime, night time, wet condition and rainy conditions. The objective of this study is to obtain the driving safety of drivers under conditions of unstable weather condition such as the rain. The visibility of road markings is closely related to the preview time and detection distances and the ways to improve road marking materials and increase the dry retroreflectivity and wet retroreflectivity, which are the measures of daytime and nighttime visibility is researched to decrease the traffic accidents. For this purpose, Road marking glass beads with the refraction rate of 1.5 and 2.2 are introduced to raise the retroreflectivity. After investigating the minimum threshold retroreflectivity and Install Minimum retroreflectivity at home and abroad, minimum control values for the roadmarking visibility and improvement of nightime rainy retroreflectivity are suggested by physical properties and retroreflectivity experiments.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1411-1412
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• 2015

Detection of road lanes is an important technology, which is being used in autonomous vehicles from last few years. This method is very helpful and supportive for the drivers to provide them safety and to avoid road accidents. Alot of methods are being used to detect road lane markings. We can categorize them into three major categories: sensor-based, feature-based, and model-based methods. And in this study we give the comprehensive survey on lane marking techniques.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.48 no.6
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• pp.15-24
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• 2011

As increase awareness of intelligent vehicle systems, many kinds of lane detection algorithm have been proposed. General boundary extraction method can bring good result in detection of lane on the road. But a shadow on the road, or other boundaries, such as horizontal lines can be detected. The method using morphological operations was used to extract information about Lane. By applying HSV color model for color information of lane, the candidate of the lane can be extracted. In this paper, the lane detection region was set by Hough transformation using the candidate of the lane. By extracting lane markings on the lane detection region, lane detection method can bring good result.

• Journal of Korea Spatial Information System Society
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• v.11 no.1
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• pp.137-144
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• 2009

Understanding lane markings in a live video captured from a moving vehicle is essential to build services for intelligent vehicles such as LDWS(Lane Departure Warning Systems), unmanned vehicles, video-based car navigation systems. In this paper, we present a novel approach to recognize the color of lane markings and the lane number that he/she is driving on. More specifically, we present a background-color removal approach to understand the color of lane markings for various illumination conditions, such as backlight, sunset, and so on. In addition, we present a probabilistic network approach to decide the lane number. According to our experimental results, the proposed idea shows promising results to detect lane number in a various illumination conditions and road environments.