Constructing an optimal decision tree for FAST corner point detection

Authors:
Abdulaziz Alkhalid;Igor Chikalov;Mikhail Moshkov
Affiliations:
King Abdullah University of Science and Technology, Thuwal, Saudi Arabia;King Abdullah University of Science and Technology, Thuwal, Saudi Arabia;King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
Venue:
RSKT'11 Proceedings of the 6th international conference on Rough sets and knowledge technology
Year:
2011

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Abstract

In this paper, we consider a problem that is originated in computer vision: determining an optimal testing strategy for the corner point detection problem that is a part of FAST algorithm [11,12]. The problem can be formulated as building a decision tree with the minimum average depth for a decision table with all discrete attributes. We experimentally compare performance of an exact algorithm based on dynamic programming and several greedy algorithms that differ in the attribute selection criterion.