Traffic Signs Recognition using CNN and Keras

Aim:

           To detect and identify the Traffic Signs detection using CNN.

 Abstract:

         Traffic sign recognition and detection are critical in expert systems for effectively recognizing traffic signs along the road, such as left hair pin bend, parking lot, minimum speed, no waiting speed. Today’s India needs traffic recognition to alert people on various signs of traffic, prevent accidents, and protect drivers along the roadway. This case of the traffic sign recognition scenario is proceeding using various techniques like deep learning, machine learning, artificial intelligence, etc. This study discusses how deep learning techniques are used to predict traffic signs. The various algorithms used for implementation are CNN and Keras. The performance of implemented algorithms calculated on accuracy as well as the ability to identify and classify traffic signs used along the roadway in real time.

 Introduction:

         Deep learning is a subset of machine learning that utilizes both structured and unstructured data to train various neural networks. Deep learning helps in detecting the traffic signs and classification needed to prevent road accidents.

          Traffic sign recognition is the latest technology used in autonomous cars and self-driving cars and is making its way into cars. It is very simply built into the cars, which many people find extremely convenient. It is an extremely helpful tool. It is fitted into the front of the car and can notify the speed limits and provide alerts on the car’s digital display to recognize traffic signs and assist drivers about their safety to prevent accidents on the roadside. It is critical that people are informed about traffic sign recognition.

          Mobileye and Continental created the first traffic sign recognition systems that recognized speed limits. It is basically divided into two categories: detection and classification. In the past few years, we have observed that the competition on the various applications used by the people has shown more interest towards this system with capability provides, like driving assistance systems.

Proposed System:

         Traffic sign recognition and detection play an equally important role in a human’s life. The primary goal of this technology is to assist drivers who are unable to recognize traffic signs on the road. As we applied CNN deep learning algorithms, we got better accuracy, which is simple and flexible and also helps in identifying and recognizing the traffic signs. Compared to existing system this performs well and takes less time.