Cyber Times International Journal of Technology & Management

Vehicle detection is a key hassle in computer vision, with several software applications which include robotics, surveillance and vehicle protection and safety. Plenty of the development of the past few years has been drive via the of availability public datasets. In this paper, we are building up an automobile detection Framework through combing histogram of oriented gradients (hog) characteristic and support vector machine (SVM). Hog feature extraction offers a reasonable and feature invariant object depiction, whereas support vector machine framework gives us a robust classifier that can manage each the training set defect and the classifier’s complexity. A detailed system framework design is offered used for detection of vehicles under different circumstances.