Journal
PATTERN RECOGNITION LETTERS
Volume 29, Issue 14, Pages 1934-1940Publisher
ELSEVIER
DOI: 10.1016/j.patrec.2008.06.006
Keywords
local feature extraction; affine invariant; 3D rotation; translation
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in this paper, we propose a gradient-based local affine invariant feature extraction algorithm (G-LAIFE), using affine moment invariants for robot localization in real indoor environments. The proposed algorithm is an effective feature extraction algorithm that is invariant to image translation and to 3D rotation, and it is within a partial range of the image scale. Representative performance analysis confirms that the proposed G-LAIFE algorithm significantly enhances the recognition rate and is more efficient than the scale invariant feature transform (SIFT), especially in terms of 3D rotation change and computational time. (c) 2008 Elsevier B.V. All rights reserved.
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