Authors:
Benoît Naegel
and
Laurent Wendling
Affiliation:
LORIA UMR 7503, Nancy University, France
Keyword(s):
Component-tree, Segmentation, Classification, Mathematical morphology, Ancient graphical drop caps.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computer Vision, Visualization and Computer Graphics
;
Data Manipulation
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Image and Video Analysis
;
Image Formation and Preprocessing
;
Mathematical Morphology
;
Methodologies and Methods
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Segmentation and Grouping
;
Sensor Networks
;
Soft Computing
Abstract:
The component-tree structure allows to analyse the connected components of the threshold sets of an image by means of various criteria. In this paper we propose to extend the component-tree structure by associating robust shape-descriptors to its nodes. This allows an efficient shape based classification of the image connected components. Based on this strategy, an original and generic methodology for object recognition is presented. This methodology has been applied to segment and recognize ancient graphical drop caps.