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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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