Real-Time Raindrop Detection Based on Deep Learning Algorithm
Keywords:
computer vision, passenger fatigue detection, Advanced Driver Assistance System
Abstract
The goal of this research is to develop an in-vehicle computerized system able to detect the raindrops on windshield and warn the driver and start the windscreen wiper in order to avoid that computer vision to acquire blurred images. This feature is important in order to develop Advanced Driver Assistance System based on computer vision. The system should be able specific scenarios that do not allow the ADAS computer vision feature to work properly. Rain drop detection will allow a more reliable Advanced Driver Assistance System.
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References
[1]. Saba N. Karbhari, Pansambal B. H., Raindrop Detection: Performance analysis of recent approaches for the use in electronic driver assistance systems.
[2]. Shladover S. E., Review of the state of development of advanced vehicle control systems, Vehicle System Dynamics, 24(6–7), p. 551-595, 1995.
[3]. Aurelien Cord, Nicolas Gimonet, Detecting Unfocused Raindrops: In-Vehicle Multipurpose Cameras, Robotics & Automation Magazine IEEE, vol. 21, no. 1, p. 49-56, 2014.
[4]. Jonathan Masci, Advances in Deep Learning for Vision, with Applications to Industrial Inspection Classification, Segmentation and Morphological extensions, Doctoral Dissertation submitted to the Faculty of Informatics of the Università della Svizzera Italiana.
[5]. Roser M., Geiger A., Video-based raindrop detection for improved image registration, in Proc. IEEE Int. Conf. Computer Vision Workshops, p. 570-577, 2009.
[6]. Jee Hun Park, Man Ho Kim, Hong Jun Im, Kyung Chang Lee and Suk Lee, Development of Vision-Based Control Smart Windshield Wiper System for Intelligent Vehicle, SICE-ICASE International Joint Conference, 2006.
[7]. Fawazi Nashashibi, Raoul De Charette de La Contrie, Alexandre Lia, Detection of Unfocused Raindrops on a Windscreen using Low-Level Image Processing, International Conference on Control, Automation, Robotics and Vision: ICARV, Dec 2010.
[2]. Shladover S. E., Review of the state of development of advanced vehicle control systems, Vehicle System Dynamics, 24(6–7), p. 551-595, 1995.
[3]. Aurelien Cord, Nicolas Gimonet, Detecting Unfocused Raindrops: In-Vehicle Multipurpose Cameras, Robotics & Automation Magazine IEEE, vol. 21, no. 1, p. 49-56, 2014.
[4]. Jonathan Masci, Advances in Deep Learning for Vision, with Applications to Industrial Inspection Classification, Segmentation and Morphological extensions, Doctoral Dissertation submitted to the Faculty of Informatics of the Università della Svizzera Italiana.
[5]. Roser M., Geiger A., Video-based raindrop detection for improved image registration, in Proc. IEEE Int. Conf. Computer Vision Workshops, p. 570-577, 2009.
[6]. Jee Hun Park, Man Ho Kim, Hong Jun Im, Kyung Chang Lee and Suk Lee, Development of Vision-Based Control Smart Windshield Wiper System for Intelligent Vehicle, SICE-ICASE International Joint Conference, 2006.
[7]. Fawazi Nashashibi, Raoul De Charette de La Contrie, Alexandre Lia, Detection of Unfocused Raindrops on a Windscreen using Low-Level Image Processing, International Conference on Control, Automation, Robotics and Vision: ICARV, Dec 2010.
Published
2020-12-15
How to Cite
1.
MARIN FB, MARIN M. Real-Time Raindrop Detection Based on Deep Learning Algorithm. The Annals of “Dunarea de Jos” University of Galati. Fascicle IX, Metallurgy and Materials Science [Internet]. 15Dec.2020 [cited 30Dec.2024];43(4):47-0. Available from: https://gup.ugal.ro/ugaljournals/index.php/mms/article/view/4038
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