Local descriptor by Zernike moments for real-time keypoint matching
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(Published version)
Date
2008
Authors
Hwang, S.K.
Billinghurst, M.
Kim, W.Y.
Editors
Li, D.
Deng, G.
Deng, G.
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Conference paper
Citation
2008 Congress on Image and Signal Processing, 2008 / Li, D., Deng, G. (ed./s), vol.2, pp.781-785
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2008 Congress on Image and Signal Processing (CISP) (27 May 2008 - 30 May 2008 : Sanya, China)
Abstract
This paper presents a real-time keypoint matching algorithm using a local descriptor derived by Zernike moments. From an input image, we find a set of key-points by using an existing corner detection algorithm. At each keypoint we extract a fixed size image patch and compute a local descriptor derived by Zernike moments. The proposed local descriptor is invariant to rotation and illumination changes. In order to speed up the computation of Zernike moments, we compute the Zernike basis functions in advance and store them in a set of lookup tables. The matching is performed with an Approximate Nearest Neighbor (ANN) method and refined by a RANSAC algorithm. In the experiments we confirmed that videos of frame size 320x240 with the scale, rotation, illumination and even 3D viewpoint changes are processed at 25~30Hz using the proposed method. Unlike existing keypoint matching algorithms, our approach also works in real-time for registering a reference image.
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Copyright 2008 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.