A Deep Neural Network Framework for Road Side Analysis and Lane Detection

Abstract

Abstract This paper presents a computer vision based framework with the aim of aiding the task of driving. The framework serves the purpose of road analysis. Road analysis is further divided into two sub-tasks. The first task aims at recognition of the different road signs, the second task aims at lane analysis. The task of automatic driving requires humans to multitask and perform many operations in split seconds. The framework is introduced to aid this task of driving if not completely automate it while keeping in mind of using it with a simple hardware and software setup. The effectiveness of the framework lies in its feature of having minimal complexity which enables it to be used in real-time. The results of the pipeline are quantified by first measuring its accuracy in the classification of road signs, second measuring its ability to gather the information about the road (lane analysis and 2 vehicle detection) thirdly by performing the time bench-marking.