Use of Machine Learning in Automobile Industry to Improve Safety Using CNN

Abstract

Abstract: Vision-based vehicle steering system cars can have three main roles: 1) road access; 2) an obstacle to find; and 3) signal recognition. The first two have already been taught many years and there have been many positive results, but a sign of traffic recognition is a less readable field. Road signs provide drivers with the most important information on the road, to do driving is safe and easy. We think road signs should play the same role of private cars. The color and shape are very different from the natural environment. The algorithm described in this paper uses this feature. It has two main parts. The first, to find, uses color range to separate image analysis and shapes to get symptoms. The second, in stages, uses the neural network. Some effects from natural forums are shown. On the other hand, the algorithm works to detect other types of marks can tell a moving robot to perform a specific task that place. Keywords: o Traffic signs o CNN o Cars o Image processing o Classification