Authors:
Tiago Candeias
;
Filipe Tomaz
and
Hamid Shahbazkia
Affiliation:
Universidade do Algarve, Portugal
Keyword(s):
Contour Extraction, Image Recognition, Document Image Analysis.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computer Vision, Visualization and Computer Graphics
;
Data Manipulation
;
Early Vision and Image Representation
;
Feature Extraction
;
Features Extraction
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Image and Video Analysis
;
Informatics in Control, Automation and Robotics
;
Methodologies and Methods
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Signal Processing, Sensors, Systems Modeling and Control
;
Soft Computing
Abstract:
The automatic extraction of closed contours is the most important and difficult problem in the automatic recognition of the Portuguese cadastral maps. Many difficulties such as gaps on contour, elements connected on contour, crossing of lines and the association of each entity to its contour have to be solved. In literature there are very few studies about the recognition of cadastral maps and the maps already studied are different than ours. Therefore our research mainly focused on appropriate computer vision algorithms that yield acceptable results. In this paper we present a sequence of algorithms to solve various problems in the contour extraction. The algorithms are completely different and each one tries to solve one specific problem of the analysis. The methods used were the Block-Fill algorithm, the Lohmann’s algorithm, the Seed-Segment algorithm and the Rosin-West’s vectorization algorithm.
The architecture of our system is presented and the results are shown at the end of
the paper.
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