DocumentCode
1122495
Title
Handling Memory Overflow in Connected Component Labeling Applications
Author
Dinstein, Its Hak ; Yen, David W.L. ; Flickner, Myron D.
Author_Institution
Department of Electrical and Computer Engineering, Ben-Gurion University, Beersheva, Israel; IBM Research Laboratory, San Jose, CA 95193.
Issue
1
fYear
1985
Firstpage
116
Lastpage
121
Abstract
The storage requirements for component labeling and feature extraction operations are unknown a priori. Whenever large images are processed, many labels, and thus a large amount of storage, may be required, making hardware implementation difficult. The proposed labeling procedure eliminates memory overflow by enabling the reuse of memory locations in which features of nonactive labels had been stored. The storage requirement for the worst case conditions is analyzed and is shown to be realizable. The basic procedure can be implemented in two modes, an interrupted mode or a parallel mode. A hardware design is presented.
Keywords
Electrons; Feature extraction; Hardware; Image storage; Labeling; Laboratories; Logic; Machine learning; Notice of Violation; Pattern recognition; Component labeling; feature extraction; image processing; visual inspection;
fLanguage
English
Journal_Title
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher
ieee
ISSN
0162-8828
Type
jour
DOI
10.1109/TPAMI.1985.4767627
Filename
4767627
Link To Document