Autonomous machines/ vehicles are all set to drive along the road. As roads get denser with other vehicles, it is difficult for drivers as well as autonomous cars to identify all the traffic signs on the path. Chances of missing out on crucial signs that may lead to fatal accidents cannot be neglected. To assists drivers and autonomous cars to overcome this problem camera-based traffic sign recognition systems are used as a part of the advanced driver assistance system (ADAS). Traffic signs play a crucial role in managing traffic on the road, disciplining the drivers, thereby preventing injury, property damage, and fatalities. Traffic sign management with automatic detection and recognition is very much part of any Intelligent Transportation System (ITS). In this era of self-driving vehicles, calls for automatic detection and recognition of traffic signs cannot be overstated. It presents a deep-learning-based autonomous scheme for cognizance of traffic signs in India. In this project, we propose a method for Traffic Sign Detection and Recognition using image processing for the detection of a sign and Convolutional Neural Networks (CNN) for the recognition of the sign. CNNs have a high recognition rate, thus making it desirable to use for implementing various computer vision tasks. TensorFlow is used for the implementation of the CNN.