Performance Bound of Position Estimation in Image Matching

Bao Shu Xu; Ze Lin Shi

doi:10.4028/www.scientific.net/KEM.500.766

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HomeKey Engineering MaterialsKey Engineering Materials Vol. 500Performance Bound of Position Estimation in Image...

Performance Bound of Position Estimation in Image Matching

Abstract:

Position estimation in image matching is a fundamental step in computer vision and image processing. To deal with the problem of performance prediction, we formulate it under statistical parameter estimation aspect. The lower bound of position estimation variance is obtained based on Cramer-Rao lower bound (CRLB) theory. This paper analyses the impact of noise to 1-D signal matching, derives the lower bound of variance, and then extends it to 2-D image matching. Furthermore, we derive numerical expression that can be computed from observed data. Finally, we use Monte Carlo simulation method to verify the derived analytical expressions. Experimental results show that the derived CRLB is tight to simulation estimated variance. The CRLB can characterize the performance bound of position estimation in image matching.

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Periodical:

Key Engineering Materials (Volume 500)

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766-772

DOI:

https://doi.org/10.4028/www.scientific.net/KEM.500.766

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Online since:

January 2012

Authors:

Bao Shu Xu, Ze Lin Shi

Keywords:

Cramer-Rao Lower Bound, Fisher Information, Image Matching, Performance Prediction

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