Refereed full papers (journals, book chapters, international conferences)

2004

@article{Hei2004a,
	vgclass =	{refpap},
	author =	{Janne Heikkil\"{a}},
	title =	{Pattern matching with affine moment descriptors},
	journal =	{Pattern Recognition},
	volume =	{37},
	number =	{9},
	pages =	{1825--1834},
	month =	{September},
	year =	{2004},
	url =	{http://dx.doi.org/10.1016/j.patcog.2004.03.005},
	abstract =	{This paper proposes a method for matching images based on
	their higher order moments without knowing the point correspondences.
	It is assumed that the disparity between the images can be explained by
	an affine transformation. The second-order statistics is used to
	transform the image points into canonical form, which reduces the
	affine matching problem for determining an orthonormal transformation
	matrix between the two point sets. Next, higher order complex moments
	are used to solve the remaining transformation. These affine moment
	descriptors are expressed in terms of the central moments of the
	original data. It is also shown that the resulting descriptors can be
	converted into affine moment invariants. A general framework for
	deriving affine moment descriptors as well as moment invariants is
	described. The experiments carried out with simulated data and real
	images indicate that the proposed method utilizing the second- and
	third-order statistics can provide good alignment results from noisy
	and spurious observations.},
}