Title :
Pattern recognition by affine Legendre moment invariants
Author :
Zhang, Hui ; Wu, Q. M Jonathan
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Windsor, Windsor, ON, Canada
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 :
computer vision; image colour analysis; image recognition; transforms; affine Legendre moment invariants; affine invariants; affine transformed image; binary image; complex moments; computer vision; geometric moments; gray image; pattern recognition; shape descriptor; Accuracy; Conferences; Databases; Image processing; Noise; Pattern recognition; Testing; Affine invariants; Legendre moments; affine transformation; pattern recognition;
Conference_Titel :
Image Processing (ICIP), 2011 18th IEEE International Conference on
Conference_Location :
Brussels
Print_ISBN :
978-1-4577-1304-0
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2011.6116676