  This paper focused on the design of an optimized object tracking technique
which would minimize the processing time required in the object detection
process while maintaining accuracy in detecting the desired moving object in a
cluttered scene. A Kalman filter based cropped image is used for the image
detection process as the processing time is significantly less to detect the
object when a search window is used that is smaller than the entire video
frame. This technique was tested with various sizes of the window in the
cropping process. MATLAB was used to design and test the proposed method. This
paper found that using a cropped image with 2.16 multiplied by the largest
dimension of the object resulted in significantly faster processing time while
still providing a high success rate of detection and a detected center of the
object that was reasonably close to the actual center.
