Title :
Skeleton-based morphological coding of binary images
Author :
Kresch, Renato ; Malah, David
Author_Institution :
Dept. of Electr. Eng., Technion-Israel Inst. of Technol., Haifa, Israel
fDate :
10/1/1998 12:00:00 AM
Abstract :
This paper presents new properties of the discrete morphological skeleton representation of binary images, along with a novel coding scheme for lossless binary image compression that is based on these properties. Following a short review of the theoretical background, two sets of new properties of the discrete morphological skeleton representation of binary images are proved. The first one leads to the conclusion that only the radii of skeleton points belonging to a subset of the ultimate erosions are needed for perfect reconstruction. This corresponds to a lossless sampling of the quench function. The second set of new properties is related to deterministic prediction of skeletonal information in a progressive transmission scheme. Based on the new properties, a novel coding scheme for binary images is presented. The proposed scheme is suitable for progressive transmission and fast implementation. Computer simulations, also presented, show that the proposed coding scheme substantially improves the results obtained by previous skeleton-based coders, and performs better than classical coders, including run-length/Huffman, quadtree, and chain coders. For facsimile images, its performance can be placed between the modified read (MR) method (K=4) and modified modified read (MMR) method
Keywords :
data compression; facsimile; image coding; image reconstruction; image representation; image sampling; mathematical morphology; binary images; coding scheme; deterministic prediction; discrete morphological skeleton representation; facsimile images; lossless binary image compression; lossless sampling; perfect reconstruction; progressive transmission scheme; quench function; radii; skeleton points; skeleton-based morphological coding; skeletonal information; ultimate erosions; Computer simulation; Fires; Gray-scale; Image analysis; Image coding; Image reconstruction; Image sampling; Morphology; Shape; Skeleton;
Journal_Title :
Image Processing, IEEE Transactions on