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Extracting Lineage Information from Hand-Drawn Ancient Maps / Ehab Essa; Xianghua Xie; Richard Turner; Matthew Stevens; Daniel Power

Image Analysis and Recognition, Volume: 9730, Pages: 268 - 275

Swansea University Author: Stevens, Matthew

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Abstract

In this paper, we present an efficient segmentation technique that extracts piecewise linear patterns from hand-drawn maps. The user is only required to place the starting and end points and the method is capable of extracting the route that connects the two, which closely colocates with the hand-dr...

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Published in: Image Analysis and Recognition
ISBN: 978-3-319-41500-0 978-3-319-41501-7
ISSN: 0302-9743 1611-3349
Published: Springer International Publishing 2016
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa49176
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Abstract: In this paper, we present an efficient segmentation technique that extracts piecewise linear patterns from hand-drawn maps. The user is only required to place the starting and end points and the method is capable of extracting the route that connects the two, which closely colocates with the hand-drawn map. It provides an effective approach to interactively process and understand those historical maps. The proposed method employs supervised learning to evaluate at every pixel location the probability that such a lineage pattern exists, followed by shortest path segmentation to extract the border of interest.
Item Description: Authored by Ehab Essa, Xianghua Xie, Richard Turner, Matthew Stevens, and Daniel Power
Keywords: computer vision, medieval history, maps
College: College of Arts and Humanities
Start Page: 268
End Page: 275