Real-time object detection and Tracking using color feature and motion

This paper, introduces a technique for automating the methodology of detecting and tracking objects utilizing color feature and motion. Video Tracking is the methodology of finding a moving object over the long distance using a camera. The main aim of video tracking is to relate target objects in consecutive video frames. The relationship can be especially troublesome when the objects are moving speedy with respect to the frame rate. An interchange situation that grows the unpredictability of the issue is the time when the tracking object changes orientation after eventually. For these circumstances video tracking frameworks typically utilize a movement model which depicts how the image of the target may change for distinctive conceivable movements of the object. In this paper an algorithm is developed to track the real-time moving objects in different frames of a video using color feature and motion.

I. Introduction

Tracking can be characterized as the problem of assessing the trajectory of an object in the picture or image plane as it moves around a scene. The requirement for high power PCs, the accessibility of high quality and modest camcorders, and the expanding requirement for automated feature analysis has produced a lot of interest for object tracking algorithms. There are three key steps in feature analysis: recognition of target moving objects, tracking of such objects from frame to frame, and analysis of object tracks to perceive their conduct. In its least complex form, tracking can be characterized as the issue of evaluating trajectory of an object in the image plane as it moves around a scene. The main goal of this investigation is to track the real time moving objects in different video frames with the assistance of a proposed algorithm. Median filtering is a non-linear operation which is utilized as a part of image processing to decrease noise. A median filter is more viable than convolution when the objective is at the same time to diminish noise and save edges.