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  4. Machine Vision Algorithms on Cadaster Plans
 
conference presentation

Machine Vision Algorithms on Cadaster Plans

Ares Oliveira, Sofia  
•
di Lenardo, Isabella  orcid-logo
2017
Premiere Annual Conference of the International Alliance of Digital Humanities Organizations (DH 2017)

Cadaster plans are cornerstones for reconstructing dense representations of the history of the city. They provide information about the city urban shape, enabling to reconstruct footprints of most important urban components as well as information about the urban population and city functions. However, as some of these handwritten documents are more than 200 years old, the establishment of processing pipeline for interpreting them remains extremely challenging. We present the first implementation of a fully automated process capable of segmenting and interpreting Napoleonic Cadaster Maps of the Veneto Region dating from the beginning of the 19th century. Our system extracts the geometry of each of the drawn parcels, classifies, reads and interprets the handwritten labels.

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Type
conference presentation
Author(s)
Ares Oliveira, Sofia  
di Lenardo, Isabella  orcid-logo
Date Issued

2017

Subjects

computer vision

•

image processing

•

cadaster

•

maps

•

document analysis

URL

URL

https://dh2017.adho.org/abstracts/169/169.pdf
Written at

OTHER

EPFL units
DHLAB  
Event nameEvent placeEvent date
Premiere Annual Conference of the International Alliance of Digital Humanities Organizations (DH 2017)

Montreal, Canada

August 8-11, 2017

Available on Infoscience
December 21, 2017
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/143531
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