JOURNAL ARTICLE

Pattern recognition by affine Legendre moment invariants

Abstract

Affine moment invariants are important shape descriptors in pattern recognition and computer vision. Existing affine invariants methods are based on geometric and complex moments. In this paper, we propose a set of affine invariants extracted from Legendre moments. These invariants are derived by the relationship between the Legendre moment of the affine transformed image and that of the original image. The performance of the proposed descriptor is evaluated with a set of binary and gray images. Experimental results show that the proposed method behaves better than existing methods in terms of pattern recognition accuracy.

Keywords:
Affine transformation Legendre polynomials Affine shape adaptation Affine hull Harris affine region detector Moment (physics) Affine combination Mathematics Affine coordinate system Artificial intelligence Pattern recognition (psychology) Image moment Set (abstract data type) Image (mathematics) Computer science Image processing Pure mathematics Affine space Mathematical analysis Physics

Metrics

6
Cited By
0.00
FWCI (Field Weighted Citation Impact)
10
Refs
0.08
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Image Retrieval and Classification Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Medical Image Segmentation Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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