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Proceedings Paper

Effects of feature characteristics and ordering in the performance of an object recognition system
Author(s): David J. Garcia
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Paper Abstract

Substantial performance gains (classification speed) are obtained in object recognition systems for large object databases if the database is pre-screened. This pre-screening process is carried out by applying successive screening filters to the database to obtain a reduced set (candidate) of objects. These filters operate on object features eliminating those objects whose features do not resemble in some sense the unknown object. The result is a reduced set of objects over which, measures of similarity are applied to obtain the unknown object's final classification. It has been observed that the order in which these screening filters are applied to the database has a noticeable effect on the size of the resulting candidate set. Additionally, the way that a particular feature partitions the pattern space (number of partitions) and the distribution of the pattern classes among the different partitions, have also substantial effects on the size of the resulting candidate set. This paper investigates the classification performance variations for different feature ordering schemes as well as the effects of the pattern distributions on the partitions in relation to the filter ordering. Experimental results showing the effects of different combinations of feature ordering and pattern partition distribution are also included.

Paper Details

Date Published: 10 June 1994
PDF: 10 pages
Proc. SPIE 2232, Signal Processing, Sensor Fusion, and Target Recognition III, (10 June 1994); doi: 10.1117/12.177764
Show Author Affiliations
David J. Garcia, IBM Corp. (United States)

Published in SPIE Proceedings Vol. 2232:
Signal Processing, Sensor Fusion, and Target Recognition III
Ivan Kadar; Vibeke Libby, Editor(s)

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