DocumentCode :
984036
Title :
Binary random fields, random closed sets, and morphological sampling
Author :
Sivakumar, Krishnamoorthy ; Goutsias, John
Author_Institution :
Dept. of Electr. & Comput. Eng., Johns Hopkins Univ., Baltimore, MD, USA
Volume :
5
Issue :
6
fYear :
1996
fDate :
6/1/1996 12:00:00 AM
Firstpage :
899
Lastpage :
912
Abstract :
We theoretically formulate the problem of processing continuous-space binary random fields by means of mathematical morphology. This may allow us to employ mathematical morphology to develop new statistical techniques for the analysis of binary random images. Since morphological transformations of continuous-space binary random fields are not measurable in general, we are naturally forced to employ intermediate steps that require generation of an equivalent random closed set. The relationship between continuous-space binary random fields and random closed sets is thoroughly investigated. As a byproduct of this investigation, a number of useful new results, regarding separability of random closed sets, are presented. Our plan, however, suffers from a few technical problems that are prominent in the continuous case. As an alternative, we suggest morphological discretization of binary random fields, random closed sets, and morphological operators, thereby effectively implementing our problem in the discrete domain
Keywords :
image sampling; mathematical morphology; random processes; set theory; statistical analysis; binary random image analysis; continuous-space binary random fields processing; discrete domain implementation; morphological discretization; morphological operators; morphological sampling; morphological transformations; random closed sets; random closed sets separability; statistical techniques; Data mining; Force measurement; Image analysis; Image processing; Image sampling; Mathematical model; Modems; Morphology; Sampling methods; Stochastic processes;
fLanguage :
English
Journal_Title :
Image Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1057-7149
Type :
jour
DOI :
10.1109/83.503907
Filename :
503907
Link To Document :
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