In contrast to the numerous edge-detection techniques that detect edge
s either point by point or using overlapping circular windows, an edge
detector using nonoverlapping rectangular windows is proposed. The de
tector examines the pixels within each rectangular window of an image,
and decides whether an edge element is present or not in the window.
Based on the gray and mass moment-preserving principles, the step edge
is estimated locally to subpixel accuracy using analytical formulas.
To apply the edge detection results to image compression, the detected
edge elements are then tracked and grouped based on proximity and ori
entation. Using the line parameters of the grouped edge elements, regi
on boundaries are approximated in a piecewise linear manner. This redu
ces the amount of data required to describe region shapes and is usefu
l for compressing some types of images. Good experimental results of c
ompressing character and trademark images are also included to show th
e feasibility of the proposed approach.