Statistical Pattern Recognition Using the Normalized Complex Moment Components Vector

Authors:
Stavros Paschalakis;Peter Lee
Affiliations:
-;-
Venue:
Proceedings of the Joint IAPR International Workshops on Advances in Pattern Recognition
Year:
2000

Citing 5
Cited 0

On digital approximation of moment invariants

Computer Vision, Graphics, and Image Processing
Optical character recognition by the method of moments

Computer Vision, Graphics, and Image Processing
On Image Analysis by the Methods of Moments

IEEE Transactions on Pattern Analysis and Machine Intelligence
Generation of moment invariants and their uses for character recognition

Pattern Recognition Letters
Noise tolerance of moment invariants in pattern recognition

Pattern Recognition Letters

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a new feature vector for statistical pattern recognition based on the theory of moments, namely the Normalized Complex Moment Components (NCMC). The NCMC will be evaluated in the recognition of objects which share identical silhouettes using grayscale images and its performance will be compared with that of a commonly used moment based feature vector, the Hu moment invariants. The tolerance of the NCMC to random noise and the effect of using different orders of moments in its calculation will also be investigated.