Motion Detection

Real time object tracking is considered as a critical application. Video object tracking has got wide application in vision, security, observational issues in natural science and in various other fields. Video surveillance for security purpose is one of its major applications. Object tracking has high priorities in religious places, market buildings, courts, train stations and airports. Various other applications include military, astronomy, road traffic regulation, robotics, medical imaging. Gesture recognition for human-machine interfaces is one of today’s hottest applications. Air traffic control is another typical application of video object tracking, where aircrafts are more or less continuously visible on radar, but in case the transponders are absent, the identity is only revealed when the pilot reports by radio. The objective of this project is to develop MATLAB programs and SIMULINK models for tracking single and multiple objects.
We present various algorithms for tracking objects and determining the velocity of moving object in sequence of frames. Using the segmentation technique we can locate a target in the current frame. Target localization in current frame was computationally much complex in the conventional algorithms. Searching an object in the current frame using these algorithms starts from its location of the previous frame in the basis of attraction probably the square of the target area, calculating weighted average for all iteration then comparing similarity coefficients for each new location. We have used various morphological operations and Blob analysis in our algorithms.
The algorithms used are Background Subtraction, Background Estimation, Optical Flow method and Adaptive Contrast Change method. The first two algorithms are simple and used for single object. The remaining two are efficient and used for multiple objects.
MATLAB is used to implement the various algorithms. We have used the Computer Vision System Toolbox in MATLAB. It has