Real-Time Lane Detection and Object Recognition in Self-Driving Car using YOLO neural network and Computer Vision
Nikita Mesvaniya1, Meghna Dhruva2, Ishita Khared3, Krishna Adhia4
1Nikita Mesvaniya, Department of Computer Engineering, Darshan Institute of Engineering and Technology, Rajkot (Gujarat), India.
2Meghna Dhruva, Department of Computer Engineering, BVM Engineering College, VVNagar, (Gujarat), India.
3Ishita Khared, Department of Computer Engineering, Darshan Institute of Engineering and Technology, Rajkot (Gujarat), India.
4Krishna Adhia, Department of Computer Engineering, Darshan Institute of Engineering and Technology, Rajkot (Gujarat), India.
Manuscript received on 26 April 2020 | Revised Manuscript received on 08 May 2020 | Manuscript Published on 22 May 2020 | PP: 87-92 | Volume-9 Issue-7S July 2020 | Retrieval Number: 100.1/ijitee.G10100597S20 | DOI: 10.35940/ijitee.G1010.0597S20
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The Darwinism of Artificial Intelligence and robotics has grown up incredibly. Recently, there are a lot of progress have been undertaken in the context of Autonomous vehicle. Robo-car or self driving car consist many module like localization and mapping, scene understanding, movement planning, and driver state. In movement planning lane perception and recognition of the object plays vital role. This proposed state-of-art recognizes the road track in the video‘s frame and perform lane detection using canny edge detector and Hough transform algorithm. In this paper, Object recognition is possible with help of YOLO (you only look once) which is one of the real time CNN methods aims to detect object inside the image as part of road track. The result manifests the road lane detection guidance and object recognition along with prediction probability and bounding box.
Keywords: Convolution Neural Network, Hough Transform, Lane Detection, Object Recognition, YOLO.
Scope of the Article: Computer Vision