Abstract
Travelling by roads is the most common and oldest way to reach the destination. The fast speed vehicles are growing each day. Many automobile industries are working on development of fast speed vehicle with various security features. Security features include safety air bags, safety breaks, and many electronic supports. But still due to various reasons vehicle crashes and road accidents happen every day. Road accidents cause loss of infrastructure and monitory. These results a lot of injuries and deaths every year in every city. Government has lot of road safety protocols, rules, and regulations to prevent road accidents. Every year government is spending a lot for road safety. This paper is presenting a smart device with various safety features. The device can be mounted in any four wheeler vehicle and can make an ordinary vehicle to semi-smart vehicle. The device is featured with monitoring of engine, tires, and other peripherals. This paper is focused on lane marking and obstacle detection on the roads. For the lane marking detection improved Hough transform, Canny edge detector has been used. And for the obstacle detection, improved CNN has been used. The algorithms are implemented on hardware and tested on real objects by mounting the device on vehicle. The developed algorithms are efficient, and results are promising.
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Suman, P., Suman, A., Jaiswal, V. (2023). A Smart Device for Automatic Detection of Lane-Marking on the Roads Using Image Processing. In: Ray, K.P., Dixit, A., Adhikari, D., Mathew, R. (eds) Proceedings of the 2nd International Conference on Signal and Data Processing. CSDP 2022. Lecture Notes in Electrical Engineering, vol 1026. Springer, Singapore. https://doi.org/10.1007/978-981-99-1410-4_44
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