The LPED (local polar edge detection) method is a newly developed 2D image processing method that
automatically utilizes the center-of-mass polar coordinate to represent, in a unique way by a 36-dimension analog
vector, the boundary of each object embedded in a picture frame. This 36D vector is the object ID for the
particular object it represents. This ID vector is independent of the position of the object and independent of the
orientation of the object, but it is a characteristic property from object to object. The background noises are
automatically filtered out if the background objects are much smaller and much more randomly distributed than the
objects of interest. This concise ID vector will not only identify the object precisely in a large picture frame where
multiple-shaped objects lie, it will also track the object automatically when the object moves and it will record the
data of movement periodically. I.e., it can measure automatically the distance of movement, the angular change of
object-orientation, and the new locations of the central of mass of the moving object between successive sampling
time intervals. In other words, it can automatically predict the near future movement of the tracked object.
The applications of this novel image processing technique, to name a few, may be (1) automatic satellite-tracking
and targeting of ground moving vehicles, (2) robotic identification of surrounding environment by some shape
selected scenic part in the environment (e.g., the cross-section of an underground tunnel) with self guidance for the
robot to go along a desired path through the whole tunnel without hitting the tunnel wall.
This paper describes the principle of LPED and some extensive experimental results, regarding the application (1)
described above, by utilizing a real-time soft-ware program designed by the author.