Affine Invariance of Non-negative Function Integral Transform

The extraction of affine invariant feature plays an important role in pattern recognition, computer vision and so on. The contour-based method cannot deal with objects with several separable components. The region-based method is usually at the expense of high computational complexity and sensitive to noise in the background of the image. In order to overcome these defects, non-negative function integral transform（NFIT） is put forward. By using NFIT and stationary wavelet transform, a novel algorithm is also constructed to extract affine invariant feature. Firstly, a general contour is constructed from the object by NFIT. Furthermore, the derived general contour is parameterized by equal area normalization method. Finally, stationary wavelet transform is applied to the obtained general contour. Simulation results show that the method not only can deal with objects with several separable components, but also have some properties of low computational complexity and robustness to noise.