Conference Paper/Proceeding/Abstract 729 views 175 downloads
Extracting Lineage Information from Hand-Drawn Ancient Maps
Ehab Essa,
Xianghua Xie 
,
Richard Turner,
Matthew Stevens ,
Daniel Power
,
Richard Turner,
Matthew Stevens ,
Daniel Power
Image Analysis and Recognition, Volume: 9730, Pages: 268 - 275
Swansea University Authors:
Xianghua Xie , Matthew Stevens
-
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DOI (Published version): 10.1007/978-3-319-41501-7_30
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...
| 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
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| Online Access: |
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| 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. |
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| Item Description: |
Authored by Ehab Essa, Xianghua Xie, Richard Turner, Matthew Stevens, and Daniel Power |
| Keywords: |
computer vision, medieval history, maps |
| Start Page: |
268 |
| End Page: |
275 |