Multiple class image-based vehicle classification using soft computing algorithms

Automatic vehicle classification has expanded into a momentous topic of study due to its importance in autonomous navigation, traffic analysis, surveillance security systems, and transportation management. This paper presents multiclass image based classification of vehicles like bikes and cars using soft computing algorithms like artificial neural network decision tree and support vector machine as well. The objective of this paper is to automate the classification of vehicles from images. A good set of descriptor features that capture the most important properties of an object are used to identify the object uniquely. Different views of vehicle images are considered as important factor during classification process as six multiple class labels are created accordingly.