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Mathematical Problems in Engineering
Volume 2012 (2012), Article ID 928161, 12 pages
http://dx.doi.org/10.1155/2012/928161
Research Article

Cutting Affine Moment Invariants

1School of Math and Statistics, Nanjing University of Information Science and Technology, Nanjing 210044, China
2School of Information Science and Technology, East China Normal University, no. 500 Dong-Chuan Road, Shanghai 200241, China

Received 18 December 2011; Accepted 26 January 2012

Academic Editor: Carlo Cattani

Copyright © 2012 Jianwei Yang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The extraction of affine invariant features plays an important role in many fields of image processing. In this paper, the original image is transformed into new images to extract more affine invariant features. To construct new images, the original image is cut in two areas by a closed curve, which is called general contour (GC). GC is obtained by performing projections along lines with different polar angles. New image is obtained by changing gray value of pixels in inside area. The traditional affine moment invariants (AMIs) method is applied to the new image. Consequently, cutting affine moment invariants (CAMIs) are derived. Several experiments have been conducted to evaluate the proposed method. Experimental results show that CAMIs can be used in object classification tasks.