
Proceedings Paper
Data acquisition from cemetery headstonesFormat | Member Price | Non-Member Price |
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Paper Abstract
Data extraction from engraved text is discussed rarely, and nothing in the open literature discusses data extraction
from cemetery headstones. Headstone images present unique challenges such as engraved or embossed characters
(causing inner-character shadows), low contrast with the background, and significant noise due to inconsistent
stone texture and weathering. Current systems for extracting text from outdoor environments (billboards, signs,
etc.) make assumptions (i.e. clean and/or consistently-textured background and text) that fail when applied to
the domain of engraved text. The ability to extract the data found on headstones is of great historical value. This
paper describes a novel and efficient feature-based text zoning and segmentation method for the extraction of
noisy text from a highly textured engraved medium. This paper also demonstrates the usefulness of constraining
a problem to a specific domain. The transcriptions of images zoned and segmented through the proposed system
have a precision of 55% compared to 1% precision without zoning, a 62% recall compared to 39%, and an error
rate of 78% compared to 8303%.
Paper Details
Date Published: 4 February 2013
PDF: 12 pages
Proc. SPIE 8658, Document Recognition and Retrieval XX, 86580I (4 February 2013); doi: 10.1117/12.2007205
Published in SPIE Proceedings Vol. 8658:
Document Recognition and Retrieval XX
Richard Zanibbi; Bertrand Coüasnon, Editor(s)
PDF: 12 pages
Proc. SPIE 8658, Document Recognition and Retrieval XX, 86580I (4 February 2013); doi: 10.1117/12.2007205
Show Author Affiliations
Cameron S. Christiansen, Brigham Young Univ. (United States)
William A. Barrett, Brigham Young Univ. (United States)
Published in SPIE Proceedings Vol. 8658:
Document Recognition and Retrieval XX
Richard Zanibbi; Bertrand Coüasnon, Editor(s)
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