DocumentCode :
1123870
Title :
Mesh-Oriented Line Drawings Theory (MOLD Theory)
Author :
Minoh, Michihiko ; Sakai, Toshiyuki
Author_Institution :
Department of Information Science, Kyoto University, Kyoto 606, Japan.
Issue :
2
fYear :
1986
fDate :
3/1/1986 12:00:00 AM
Firstpage :
210
Lastpage :
221
Abstract :
In this paper, we describe a new model of bilevel digital images of line drawings. The key idea is that the constraints of generating the line drawings are available to select patterns which are considered to be a certain local appearance of line drawings. Concretely, when a bilevel digital image of line drawings is observed by 3 × 3 pixels´ unit mesh, the patterns occurring in the unit mesh are restricted by the constraints that the digital image is line-structured. At first, lines in a digital image are strictly defined and then two assumptions related to the minimum line width and observing unit mesh are introduced. It is theoretically derived what kinds of patterns occur under these conditions and we call them ``legal patterns,´´ while the other patterns not satisfying above conditions are called ``illegal patterns.´´ Next, new representations such as SYM pictures and LSC pictures, which consist only of legal patterns, are proposed as a model of bilevel digital images of line drawings and the algorithms to transcribe the original bilevel digital image into the new representations in the model are introduced. Finally, the experimental results are evaluated from the viewpoint of the amount of data involved in the new representations. The results show that our theory is well-fitted to actual images and that many useful and practical applications will be derived not only in the field of documents processing, but also of digital communication.
Keywords :
Application software; Data compression; Design automation; Digital communication; Digital images; Humans; Law; Legal factors; Office automation; Pixel; Bilevel image; data compression; legal patterns; line drawings; model representation;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/TPAMI.1986.4767774
Filename :
4767774
Link To Document :
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