Radial Tchebichef moment invariants for image recognition

Authors:
Bin Xiao;Jian-Feng Ma;Jiang-Tao Cui
Affiliations:
The Key Laboratory of Computer Networks and Information Security, Ministry of Education, Xidian University, Xi'an 710071, China and School of Physics & Electrical Information Engineering, Ningxia ...;The Key Laboratory of Computer Networks and Information Security, Ministry of Education, Xidian University, Xi'an 710071, China;The Key Laboratory of Computer Networks and Information Security, Ministry of Education, Xidian University, Xi'an 710071, China
Venue:
Journal of Visual Communication and Image Representation
Year:
2012

Citing 9
Cited 1

Invariant Image Recognition by Zernike Moments

IEEE Transactions on Pattern Analysis and Machine Intelligence
Image reconstruction from a complete set of similarity invariants extracted from complex moments

Pattern Recognition Letters
Translation and scale invariants of Tchebichef moments

Pattern Recognition
Image Analysis Using Hahn Moments

IEEE Transactions on Pattern Analysis and Machine Intelligence
Construction of a complete set of orthogonal Fourier-Mellin moment invariants for pattern recognition applications

Image and Vision Computing
Image analysis by Bessel-Fourier moments

Pattern Recognition
Combined invariants to blur and rotation using Zernike moment descriptors

Pattern Analysis & Applications
Image analysis by Tchebichef moments

IEEE Transactions on Image Processing
Image analysis by Krawtchouk moments

IEEE Transactions on Image Processing

Generic radial orthogonal moment invariants for invariant image recognition

Journal of Visual Communication and Image Representation

Quantified Score

Hi-index	0.00

Visualization

Abstract

Radial Tchebichef moments as discrete orthogonal moments in the polar coordinate have been successfully used in the field of image recognition. However, the scale invariant property of these moments has not been studied due to its complexity of the problem. In this paper, we present a method to construct a set of scale and rotation invariants extracted from radial Tchebichef moments, named radial Tchebichef moment invariants (RTMI). Experimental results show the efficiency and the robustness to noise of the proposed method for recognition tasks.