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Proceedings Paper

Comparison of five types of synthetic estimation filters for pose parameter estimation
Author(s): Marian K. Bennett; P. Karivaratha Rajan
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Paper Abstract

Synthetic estimation filters, introduced by Juday and Monroe, have been shown to be very useful in the estimation of pose parameters of objects from their images. These filters are designed from a composite image made up of a linear combination of images which have undergone variations in their position by a known amount. Each filter is designed such that its response for each of the constituent images lies on a straight line. The peak response of the filter was chosen as the response of interest. Though these filters were designed to have an affine response with respect to the pose parameter, the resulting response in general is not affine and this causes considerable error in the estimate. On a detailed study of the SEF filter design, it is found that this discrepancy results because of the use of the maximum response of the filter rather than the response at the origin. Hence, in this paper, new types of synthetic estimation filters constructed on the basis of the filter response at the origin are proposed. These filters, except the phase-only filters, yield exactly the desired response for the constituent images. Three filters of this type -- matched, phase-only, and composite phase filters -- are considered in this paper. Simulation results conducted on these filters using a set of images are presented. The accuracy of estimation is compared with the previous two SEFs - - matched and phase-only filters. It is found that the new filters possess better estimation accuracy. Noise analysis of these filters were also carried out. Both analytical and simulation studies were made. The matched SEFs designed on the basis of the response at the origin were found to possess good noise resistance characteristics.

Paper Details

Date Published: 1 July 1992
PDF: 11 pages
Proc. SPIE 1702, Hybrid Image and Signal Processing III, (1 July 1992); doi: 10.1117/12.60551
Show Author Affiliations
Marian K. Bennett, Tennessee Technological Univ. (United States)
P. Karivaratha Rajan, Tennessee Technological Univ. (United States)


Published in SPIE Proceedings Vol. 1702:
Hybrid Image and Signal Processing III
David P. Casasent; Andrew G. Tescher, Editor(s)

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