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Proceedings Paper

Automation of digital historical map analyses
Author(s): Tenzing W. Shaw; Peter Bajcsy
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Paper Abstract

This paper addresses the problem of automating analyses of historical maps. The problem is motivated by the lack of accuracy and consistency in the current comparison process of geographical objects found in historical maps by visual inspections. The objective of our work is to compare shape characteristics of the Great Lakes region in a dataset of approximately 40 French and British historical maps created in the 17th through the 19th centuries. Our approach decomposes the visual inspection into steps such as object segmentation, spatial scale calibration, extraction of calibrated object descriptors and comparison of descriptors over time and multiple cartographer houses. The automation of object segmentation is achieved by template shape-based segmentation using the Hu moments as shape descriptors and ball-based region growing. The automation of spatial calibration is accomplished by detection and classification of lines along map borders and by mapping striped boundaries intersected by latitude and longitude lines into degrees of arc length. Thus, shape characteristics of segmentation results in pixels can be converted to geographical units, for example, an area of a lake in square miles. We report experimental evaluations of automation accuracy based on comparison with manual segmentation results, as well as the knowledge obtained from the area comparisons.

Paper Details

Date Published: 8 March 2011
PDF: 10 pages
Proc. SPIE 7869, Computer Vision and Image Analysis of Art II, 78690A (8 March 2011); doi: 10.1117/12.872875
Show Author Affiliations
Tenzing W. Shaw, Univ. of Illinois at Urbana-Champaign (United States)
Peter Bajcsy, Univ. of Illinois at Urbana-Champaign (United States)

Published in SPIE Proceedings Vol. 7869:
Computer Vision and Image Analysis of Art II
David G. Stork; Jim Coddington; Anna Bentkowska-Kafel, Editor(s)

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