Letter-level shape description by skeletonization in faded documents

R. Singh, M. C. Wade, N. P. Papanikolopoulos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations


We present a method for determining the skeletal shape description for letters in texts faded due to ageing and/or poor ink quality. The proposed algorithm is interesting in that it neither involves assumptions about demarcation of object regions from the background, nor does it require pixel connectivity in the text regions. Consequently, it may be applied for obtaining the shape descriptions of sparse regions, which are characteristic of letters in faded documents. Given the pixel distribution for a letter or a word from a faded document, the method involves an iterative evolution of a piecewise-linear approximation of the principal curve of this pixel distribution. By constraining the principal curve to lie on the edges of the Delaunay triangulation of the shape distribution, the adjacency relationships between regions in the shape can be detected and used in evolving the skeleton. The approximation of the principal curve, on convergence, gives the final skeletal shape. The skeletonization is invariant to Euclidean transformations and is adaptive in terms of the topology of the underlying shape distribution as well as in the number of units needed for the piece-wise approximation of the principal curve.

Original languageEnglish (US)
Title of host publicationProceedings - 4th IEEE Workshop on Applications of Computer Vision, WACV 1998
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)0818686065, 9780818686061
StatePublished - 1998
Event4th IEEE Workshop on Applications of Computer Vision, WACV 1998 - Princeton, United States
Duration: Oct 19 1998Oct 21 1998

Publication series

NameProceedings - 4th IEEE Workshop on Applications of Computer Vision, WACV 1998


Other4th IEEE Workshop on Applications of Computer Vision, WACV 1998
Country/TerritoryUnited States

Bibliographical note

Funding Information:
The authors would like to thank Vladimir Cherkassky, who has participated in and co-authored [16], the skeletonization algorithm. Thanks are due to the James J. Hill Reference Library, St. Paul Minnesota for the faded text used as an example in this paper. This research was supported by the NSF through Grants #IRI-9410003 and #IRI-9502245.

Publisher Copyright:
© 1998 IEEE.


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