DocumentCode
1471043
Title
Optimal correspondence of string subsequences
Author
Wang, Ynjiun P. ; Pavlidis, Theo
Author_Institution
Dept. of Comput. Sci., State Univ. of New York, Stony Brook, NY, USA
Volume
12
Issue
11
fYear
1990
fDate
11/1/1990 12:00:00 AM
Firstpage
1080
Lastpage
1087
Abstract
The definition of optimal correspondent subsequence (OCS), which extends the finite alphabet editing error minimization matching to infinite alphabet penalty minimization matching, is given. The authors prove that the string distance derived from OCS is a metric. An algorithm to compute the string-to-string OCS is given. The computational complexity of OCS is analyzed. OCS is more efficient than relaxation and elastic matching for 1D problems. An algorithm combining syntactic information in template matching is given to show the ease of integrating regular grammar into the OCS technique. Since in different applications different penalty functions may be required, two of them are discussed: one pointwise and the other piecewise. The pointwise application consists of a stereo epipolar line matching problem solved by using string-to-string OCS. The feasibility of applying OCS to UPC bar-code recognition is investigated, showing the elegance of string-to-regular-expression OCS compared to the relaxation and elastic matching techniques
Keywords
computational complexity; optimisation; pattern recognition; UPC bar-code recognition; computational complexity; elastic matching; finite alphabet editing error minimization matching; infinite alphabet penalty minimization matching; metric; optimal correspondent subsequence; regular grammar; relaxation; stereo epipolar line matching problem; string distance; string subsequences; string-to-regular-expression subsequence; string-to-string subsequence; syntactic information; template matching; Computational complexity; Computer science; Helium; Image recognition; Noise level; Pattern matching; Pattern recognition; Quantization; Speech analysis; Speech recognition; Stereo vision;
fLanguage
English
Journal_Title
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher
ieee
ISSN
0162-8828
Type
jour
DOI
10.1109/34.61707
Filename
61707
Link To Document