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Proceedings Paper

Application Of An Iterative Feature Matching Algorithm To Terminal Homing
Author(s): E. Noges; A. M. Savol; A. J. Witsmeer; D. Moerdyke
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Paper Abstract

Target recognition in the terminal homing scenario consists of matching a set of sensed features with a set of reference features in the prestored reference feature map. An efficient feature matching algorithm, MACHAL, is described. This iterative algorithm employs clustering of feature metrics rather than exhaustive correlation calculations between reference and sensed features. Clustering, followed by data thinning, quickly reduces both reference and sensed data sets and thereby reduces the computational burden. MACHAL is a general algorithm which is capable of matching feature vectors of arbitrary dimension. The computational requirements increase with the dimension of the feature space and with thE increasing number of feature vectors in the sensed and reference feature sets. In this paper, MACHAL is applied to a low order feature matching in a relatively sparse feature space, characteristic of terminal homing problems. A probability model for the algorithm is developed and its validity tested by Monte Carlo simulation. Upper bounds for the clustering threshold and for the noise variance are developed using the probability model. The performance of the algorithm is evaluated by assessment of match accuracy, and robustness to noise resulting from typical sets of sensed and reference scenes. The application of MACHAL to higher order feature space is demonstrated.

Paper Details

Date Published: 23 December 1980
PDF: 12 pages
Proc. SPIE 0238, Image Processing for Missile Guidance, (23 December 1980); doi: 10.1117/12.959153
Show Author Affiliations
E. Noges, Boeing Aerospace Company (United States)
A. M. Savol, Boeing Aerospace Company (United States)
A. J. Witsmeer, Boeing Aerospace Company (United States)
D. Moerdyke, Boeing Aerospace Company (United States)


Published in SPIE Proceedings Vol. 0238:
Image Processing for Missile Guidance
Thomas F. Wiener, Editor(s)

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