Support vector machine application on vehicles

In this paper, methods of choosing a vehicle out of an image are explored. Digital images are taken from a monocular camera. Image processing techniques are applied to each single frame picture to create the feature vector. Finally the resulting features are used to classify whether there is a car in the picture or not using support vector machines. The results are compared to those obtained using a neural network. A discussion on techniques to enhance the feature vector and the results from both learning machines will be included.