Title :
Robust morphological representation of binary images
Author :
Schonfeld, Dan ; Goutsias, John
Author_Institution :
Dept. of Electr. & Comput. Eng., Johns Hopkins Univ., Baltimore, MD, USA
Abstract :
A general theory for the morphological representation of discrete and binary images is presented. Particular cases of the general scheme are shown to yield a number of useful image representations. The effect of noise degradation is studied. It is proven that, under certain assumptions, the general reduced morphological skeleton is the best morphological representation among a collection of invertible morphological image representations. This representation results in a minimal upper-bound on the average probability of error of reconstructing a binary image from its noisy representation
Keywords :
encoding; interference (signal); pattern recognition; picture processing; binary images; invertible morphological image representations; noise degradation; Constraint theory; Degradation; Image analysis; Image coding; Image reconstruction; Image representation; Laboratories; Noise robustness; Skeleton; Working environment noise;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1990. ICASSP-90., 1990 International Conference on
Conference_Location :
Albuquerque, NM
DOI :
10.1109/ICASSP.1990.115934
