Moving Objects Detection and Tracking in Using Improved Odd frame Difference and Camshift Algorithm

At present, detection and tracking for moving objects from video sequences have been implemented in many fields due to its important role. Video surveillance, medical imaging, robot vision, traffic monitoring, biomedical image analysis, and others are among the fields on which object detection and tracking are applied. Different algorithms used, where background subtraction and frame differencing are most efficient for moving objects detections, and Camshift method for tracking. Traditional frame differencing tends to cause the noise in an image and false alarms, normally when the illumination changes. This paper presented the improved odd frame difference techniques which reduce the noise and false alarms in detects moving objects and tracking moving objects using Camshift techniques. The techniques use the odd frame difference, mean of the difference set thresholds and the global thresholds using the bitwise OR operator. The binary image presents the foreground if the consecutive sequence of binary intersects and the result is HIGH, 1. The results obtained eradicate the effects caused by the traditional frame differencing, and it sounds the accuracy and efficiency of the techniques in detecting and tracking moving objects in the video sequences in the camera.