Construction of a complete set of orthogonal Fourier-Mellin moment invariants for pattern recognition applications

Authors:
H. Zhang;H. Z. Shu;P. Haigron;B. S. Li;L. M. Luo
Affiliations:
Laboratory of Image Science and Technology, School of Computer Science and Engineering, Southeast University, 210096 Nanjing, China;Laboratory of Image Science and Technology, School of Computer Science and Engineering, Southeast University, 210096 Nanjing, China and Centre de Recherche en Information Biomédicale Sino-fra ...;INSERM U642, 35042 Rennes, France and Laboratoire Traitement du Signal et de l'Image, Université de Rennes I, 35042 Rennes, France and Centre de Recherche en Information Biomédicale Sino ...;Department of Radiation Oncology, Shandong Cancer Hospital, 250117 Jinan, China;Laboratory of Image Science and Technology, School of Computer Science and Engineering, Southeast University, 210096 Nanjing, China and Centre de Recherche en Information Biomédicale Sino-fra ...
Venue:
Image and Vision Computing
Year:
2010

Citing 13
Cited 5

On Image Analysis by the Methods of Moments

IEEE Transactions on Pattern Analysis and Machine Intelligence
Invariant Image Recognition by Zernike Moments

IEEE Transactions on Pattern Analysis and Machine Intelligence
Orthogonal Moment Features for Use With Parametric and Non-Parametric Classifiers

IEEE Transactions on Pattern Analysis and Machine Intelligence
Zernike moment-based image analysis and its application

Pattern Recognition Letters
Robust and efficient Fourier-Mellin transform approximations for Gray-level image reconstruction and complete invariant description

Computer Vision and Image Understanding
Image reconstruction from a complete set of similarity invariants extracted from complex moments

Pattern Recognition Letters
Fast Zernike wavelet moments for Farsi character recognition

Image and Vision Computing
Translation and scale invariants of Tchebichef moments

Pattern Recognition
Geometric moment invariants

Pattern Recognition
Subpixel edge location based on orthogonal Fourier-Mellin moments

Image and Vision Computing
Numerical experiments on the accuracy of rotation moments invariants

Image and Vision Computing
Radial and Angular Moment Invariants for Image Identification

IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognitive Aspects of Moment Invariants

IEEE Transactions on Pattern Analysis and Machine Intelligence

Quaternion Fourier-Mellin moments for color images

Pattern Recognition
Radial Tchebichef moment invariants for image recognition

Journal of Visual Communication and Image Representation
Generic radial orthogonal moment invariants for invariant image recognition

Journal of Visual Communication and Image Representation
Quaternion Bessel-Fourier moments and their invariant descriptors for object reconstruction and recognition

Pattern Recognition
Region and boundary feature estimation on ultrasound images using moment invariants

Computer Methods and Programs in Biomedicine

Quantified Score

Hi-index	0.00

Visualization

Abstract

The completeness property of a set of invariant descriptors is of fundamental importance from the theoretical as well as the practical points of view. In this paper, we propose a general approach to construct a complete set of orthogonal Fourier-Mellin moment (OFMM) invariants. By establishing a relationship between the OFMMs of the original image and those of the image having the same shape but distinct orientation and scale, a complete set of scale and rotation invariants is derived. The efficiency and the robustness to noise of the method for recognition tasks are shown by comparing it with some existing methods on several data sets.