Image classification using separable invariant moments of Krawtchouk-Tchebichef

In this paper, we propose a new set of separable two-dimensional discrete orthogonal moments called Krawtcouk-Tchebichef's moments. This set of moments is based on the bivariate discrete orthogonal polynomials defined from the product of Krawtchouk and Tchebichef discrete orthogonal polynomials...

Full description

Saved in:
Bibliographic Details
Main Authors: Sayyouri, M., Hmimid, A., Karmouni, H., Qjidaa, H., Rezzouk, A.
Format: Conference Proceeding
Language:English
Subjects:
Acceleration
Algebra
Classification
Color
Conferences
Electronics
Gray-scale
Image analysis
Image classification
Invariants
Krawtchouk-Tchebichef's invariant moments
Mathematical model
Pattern recognition
Polynomials
Representations
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this paper, we propose a new set of separable two-dimensional discrete orthogonal moments called Krawtcouk-Tchebichef's moments. This set of moments is based on the bivariate discrete orthogonal polynomials defined from the product of Krawtchouk and Tchebichef discrete orthogonal polynomials with one variable. We also present a novel set of Krawtchouk-Tchebichef invariant moments. These invariant moments are derived algebraically from the geometric invariant moments and their computation is accelerated using an image representation scheme. The performance of these invariant moments used as pattern features for a pattern classification is compared with Tchebichef and Krawtchouk invariant moments.
ISSN:2161-5330
DOI:10.1109/AICCSA.2015.7507142