Performance Analysis of Vehicle Detection and Verification Using Resolution Transform
I Nithya · 2014
Most of the accidents are caused by other cars, and also for the improvement of road safety vehicle detection arises as the key challenge for ADAS(advanced driver assistance systems). Most of the methods address vehicle detection in two stages, namely hypothesis generation and hypothesis verification. In the first stage to detect the vehicle based on some expected feature of vehicles, such as color, shadow, vertical edges , or motion. The aim of the second stage is to verify the correctness of the vehicle candidates provided by the hypothesis generation stage. The objectives of the project includes, [1]Detect the moving object in a real time video environment. [2] Classify the vehicle type based on its templates. [3] Analyze its performance. In practical applications, however there are many factors that make the problem complex such as illumination variation, appearance change, shape deformation, partial occlusion, and camera motion. Moreover, lots of these applications require a realtime response. Therefore the development of realtime working algorithms is of essential importance.