IMPLEMENTATION OF VEHICLE DETECTION AND TRACKING USING MACHINE LEARNING TECHIQUE

To identify the objects within an image and to locate it and catch or to find the instance of objects , object detection is a technology used with sensors for a group of images or videos. Machine learning is a computer vision technology that pivots on identifying and labeling objects with images. Detection of vehicle by sensing is a technology of the behavior of machines rather than human view. In recent days vehicle detection is the major features by companies and organizations. The methods that allow computers to visualize and understand the information using logical thinking to find solution for the real-world problems or issues can be applied detection can be used to identify an object in the video or real-world environment via camera. The detection of vehicle applies in trace the vehicle, average speed of each individual vehicle, traffic control, developing parking sensors and other devices. The implementation of the methods discussed in this paper for detecting and tracking the vehicle is done with OpenCV and python to detect and track the vehicle automatically. Among many algorithms of Support Vector Machine (SVM) classifiers Linear SVC is used to predict vehicles and decision tree to develop for detection and tracking tasks. The subsample of pigs is used to implement the sliding window approach.