Moving vehicles classification in WEKA

Vehicle classification has crop up as an important field of study due of its importance in variety of applications like surveillance, security framework, traffic congestion prevention and accidents avoidance etc. The image sequences for traffic scenes are recorded by a stationary NI smart camera. The video clip is processed in LabVIEW to detect vehicle and measure characteristics like width, length, area, perimeter using image process feature extraction techniques. The extracted vehicle features from the traffic video are used to build a neural network classifier model in WEKA data mining toolbox. The classifier model implements multi layer perceptron (MLP) technique, a classification method of data mining. A feed-forward neural network (NN) is trained to classify vehicles in WEKA using the vehicle features of traffic video. The classifier model is used to classify new vehicles instances as big or small based on the vehicle features in images.