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%.

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)