NDLI: Interest points detection based on local frequency information of an image

Content Provider	IEEE Xplore Digital Library
Author	Khan, J.F. Adhami, R.R. Bhuiyan, S.M.A.
Copyright Year	2008
Description	Author affiliation: Univ. of Alabama in Huntsville, Huntsville (Khan, J.F.; Adhami, R.R.; Bhuiyan, S.M.A.)
Abstract	In this paper we propose a novel technique for detecting rotation and scale invariant interest points from the local frequency representation of an image. Local or instantaneous frequency is the spatial derivative of the local phase, where the local phase of any signal can be found from its Hilbert transform. Local frequency estimation can detect edge, ridge, corner and texture information at the same time and shows high values at those dominant features of an image. For each pixel, we select an appropriate width of the window for computing the derivative of the phase. In order to select the width of the window for any given pixel, we make use of the measure of the extent to which the phases, in the neighborhood of that pixel, are in the same direction. The local frequency map, thus obtained, is then thresholded by employing a global thresholding approach to detect the interest or feature points. Repeatability rate, a performance evaluation criterion for an interest points detector, is used to check the geometric stability of the proposed method under different transformations. We present simulation results of the detection of feature points from an image and the repeatability rate as a function of image rotation and scale changes. The results prove the efficacy of the proposed feature points detection algorithm.
Starting Page	569
Ending Page	574
File Size	543049
Page Count	6
File Format	PDF
ISBN	9781424418831
DOI	10.1109/SECON.2008.4494358
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-04-03
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image edge detection Detectors Computer vision Parametric statistics Frequency estimation Phase measurement Stability criteria Detection algorithms Terminology Robustness interest point Hilbert transform affine invariant repeatability rate scale selection
Content Type	Text
Resource Type	Article

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