Real Time Indian Traffic Sign Detection using Image Processing and CNN

Abstract

Driver Assistance and Monitoring System plays a very important role in traffic management especially in Indian roads. It eventually reduces the accidents and major injuries. DAMS (Driver Assistance and Monitoring System) give the safety and driving comfort. The main motto of our work is to design the effective methodology for the assistance and driver monitoring system which alerts the driver when it detects the road signs so that driver can take the appropriate action. The proposed methodology detects a road signs which is present in the dataset under cluttered background and different lighting conditions. The proposed work detecting the road sign based on colour and shape. The edge of the road sign is detected using canny edge operator. The images are enhanced and removed the noise using median filters. The images are classified as stop, no entry, speed limit using Convolutional Neural Network (CNN) classifier.