Traffic Sign Recognition using CNN
Author(s):
Jonah Jacob Oommen, Dr. Manju Khanna, Himanshu Upadhyay, Koshal Bothra
Keywords:
Traffic Sign Detection, Vision Based Framework, Indian Sign, Traffic Sign
Abstract
Traffic signs are utilized as a method of warning and guiding drivers, helping to regulate the flow of traffic among vehicles, pedestrians, motorcycles, bicycles and others who travel the streets, highways and other roadways. In an attempt to focus on the road while driving, drivers often miss out on signs on the side of the road, which could be dangerous for them and for the people around them. Many road accidents occur due to lack of traffic signs. Detecting and classifying different group of traffic signs can save our lives as well as resources. In this paper a vision-based framework is presented which detects and recognizes traffic signs inside the attentional visual field of drivers. The properties of road and traffic signs and their implications for image processing for the recognition task are understood. The various tasks necessary for this paper is to understand color, color spaces and color space conversion, to develop robust color segmentation algorithms that can be used in a wide range of environmental conditions, to develop a recognizer that is invariant to in-plane transformations such as translation, rotation, and scaling based on invariant shape measures and to evaluate the performance of the aforementioned methods for robustness under different conditions of weather, lighting geometry, and sign.
Article Details
Unique Paper ID: 152266

Publication Volume & Issue: Volume 8, Issue 2

Page(s): 679 - 683
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