Authors:
Faten Chaieb
and
Faouzi Ghorbel
Affiliation:
Ecole Nationale des Sciences de l’Informatique (ENSI), CRISTAL Laboratory, GRIFT, Tunisia
Keyword(s):
Projective invariance, descriptors, completeness, stability, planar contours, shape recognition.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Data Manipulation
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Methodologies and Methods
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Soft Computing
Abstract:
Planar shapes recognition is an important problem in computer vision and pattern recognition. We deal with planar shape contour views that differ by a general projective transformation. One method for solving such problem is to use projective invariants. In this work, we propose a projective and parameterization invariant generation framework based on the harmonic analysis theory. In fact, invariance to reparameterization is obtained by a projective arc length curve reparameterization process. Then, a complete and stable set of projective harmonic invariants is constructed from the Fourier coefficients computed on the reparameterized contours. We experiment this set of descriptors on analytic contours in order to recognize projectively similar ones.