Document Server@UHasselt >
Research >
Research publications >

Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/8029

Title: A scale invariant detector based on local energy model for matching images
Authors: ANCUTI, Cosmin
BEKAERT, Philippe
Issue Date: 2007
Citation: Skala, V. (Ed.) 15th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision. p. 143-150.
Series/Report: JOURNAL OF WSCG, 15(1-3)
Abstract: Finding correspondent feature points represents a challenge for many decades and has involved a lot of preoccupation in computer vision. In this paper we introduce a new method for matching images. Our detection algorithm is based on the local energy model, a concept that emulates human vision system. For true scale invariance we extend this detector using automatic scale selection principle. Thus, at every scale level we identify points where Fourier components of the image are maximally in phase and then we extract only feature points that maximize a normalized derivatives function through scale space. To find correspondent points a new method based on the Normalized Sum of Squared Differences (NSSD) is introduced. NSSD is a classical matching measure but is limited to only the small baseline case. Our descriptor is adapted to characteristic scale and also is rotation invariant. Finally, experimental results demonstrate that our algorithm is reliable for significant modification of scale, rotation and variation of image illumination.
Notes: Date: Jan 29 - Feb 2, 2007
URI: http://hdl.handle.net/1942/8029
ISI #: 000260374900019
ISBN: 978-80-86943-00-8
ISSN: 1213-6972
Category: C1
Type: Proceedings Paper
Validation: ecoom, 2009
Appears in Collections: Research publications

Files in This Item:

Description SizeFormat
N/A959.01 kBAdobe PDF

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.