Abstract
As a result of road traffic crashes, approximately 1.35 million people die each year, and between 40 to 70 million are injured drastically. Most of these accidents occurs because of to lack of response time to instant traffic events. To develop such recognition and detection system in autonomous cars, it is important to monitor and guide driver through real time traffic events. This involves Road sign recognition and road lane detection. In order to make the driving process safer and efficient, a plan is made to design a driver-assistance system with road sign recognition and lane detection features. In this system we have focused on two important aspects, Road sign recognition and lane detection. The process of road sign recognition in a video can be broken into two main areas for research; detection and classification using convolutional neural networks. Road signs will be detected by analysing colour information, which can be red and blue, contained on the images whereas, in classification phase the signs are classified according to their shapes and characteristics. Along with road sign recognition we also focused on Road Lane detection which is one significant method in the visualization-based driver support structure and capable to be used for vehicle guiding and monitoring, road congestion avoidance, crash avoidance.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: International Journal for Research in Applied Science and Engineering Technology
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.