Authors:
Celia Salmim Rafael
1
and
Jorge Simao
2
Affiliations:
1
ESTM, IPLeiria, Portugal
;
2
DCC-Faculty of Sciences-University of Porto, Portugal
Keyword(s):
Pattern Analysis and Recognition, Geometry Visual Recognition, Mathematical Expression Visual Recognition, Symbol and Structure Recognition.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Feature Extraction
;
Features Extraction
;
Image and Video Analysis
;
Informatics in Control, Automation and Robotics
;
Segmentation and Grouping
;
Signal Processing, Sensors, Systems Modeling and Control
;
Structural and Syntactic Approach
Abstract:
We describe a system that uses image processing and computer vision techniques to discover and recognize mathematical, logical, geometric, and other structures and symbols from bit-map images. The system uses a modular architecture to allow easy incorporation of new kinds of object recognizers. The systems uses a ``blackboard'' data-structure to retain the list of objects that have been recognized. Particular object recognizers check this list to discover new objects. Initially, objects are simple pixel clusters resulting from image-processing and segmentation operations. First-level object recognizers include symbol/character recognizers and basic geometric elements. Higher-level object recognizers collect lower-level objects and build more complex objects. This includes mathematical-logical expressions, and complex geometric elements such as polylines, graphs, and others. The recognized objects and structures can be exported to a variety of vector graphic languages and type-settin
g systems, such as SVG and LaTeX.
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