Integration Methode of Circle Hough Transform, 2DPCA and Artificial Neural Network for Recognition Model of Wheel Vehicle

Abstract

Detection and recognition vehicles are important things in the transportation systems such as analysis traffic control and fees policy. In order to recognize the vehicle, it needs some features to recognize them such as shape, police number and wheel. This research using side view of vehicle image to recognize the vehicle from its wheels. The purpose of research is to build recognition model of wheel using Circle Hough Transform (CHT), 2DPCA and Artificial Neural Network. The CHT used to detect the circle of wheel in the image, 2DPCA for feature exctraction and Artificial Neural Network to recognize the wheels. The result of the research is the accuracy level of success and the error for wheel recognition. The error consist of two parts including the miss and the false alarm rate. In this research, the highest accuracy of success is 94,4% with 100 neuron in the hidden layer. Its also being tested data with noise and fake circle.