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Sensors 2016, 16(12), 2160; doi:10.3390/s16122160

Recognition of Damaged Arrow-Road Markings by Visible Light Camera Sensor Based on Convolutional Neural Network

Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, Seoul 100-715, Korea
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Author to whom correspondence should be addressed.
Academic Editor: Felipe Jimenez
Received: 31 October 2016 / Revised: 7 December 2016 / Accepted: 14 December 2016 / Published: 16 December 2016
(This article belongs to the Special Issue Sensors for Autonomous Road Vehicles)
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Abstract

Automobile driver information as displayed on marked road signs indicates the state of the road, traffic conditions, proximity to schools, etc. These signs are important to insure the safety of the driver and pedestrians. They are also important input to the automated advanced driver assistance system (ADAS), installed in many automobiles. Over time, the arrow-road markings may be eroded or otherwise damaged by automobile contact, making it difficult for the driver to correctly identify the marking. Failure to properly identify an arrow-road marker creates a dangerous situation that may result in traffic accidents or pedestrian injury. Very little research exists that studies the problem of automated identification of damaged arrow-road marking painted on the road. In this study, we propose a method that uses a convolutional neural network (CNN) to recognize six types of arrow-road markings, possibly damaged, by visible light camera sensor. Experimental results with six databases of Road marking dataset, KITTI dataset, Málaga dataset 2009, Málaga urban dataset, Naver street view dataset, and Road/Lane detection evaluation 2013 dataset, show that our method outperforms conventional methods. View Full-Text
Keywords: arrow-road marking recognition; convolutional neural network; damaged arrow-road marking; visible light camera sensor; advanced driver assistance system (ADAS) arrow-road marking recognition; convolutional neural network; damaged arrow-road marking; visible light camera sensor; advanced driver assistance system (ADAS)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Vokhidov, H.; Hong, H.G.; Kang, J.K.; Hoang, T.M.; Park, K.R. Recognition of Damaged Arrow-Road Markings by Visible Light Camera Sensor Based on Convolutional Neural Network. Sensors 2016, 16, 2160.

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