A wavelet based multiresolution algorithm for rotation invariant feature extraction

Ch. S. Sastry

doi:10.1016/j.patrec.2004.07.011

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A wavelet based multiresolution algorithm for rotation invariant feature extraction

2004-12-01

PRE

Ch. S. Sastry

Arun K. Pujari

Chakravarthy Bhagvati

DOI：10.1016/j.patrec.2004.07.011

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Abstract

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The present work aims at proposing a new wavelet representation formula for rotation invariant feature extraction. The algorithm is a multilevel representation formula involving no wavelet decomposition in standard sense. Using the radial symmetry property, that comes inherently in the new representation formula, we generate the feature vectors that are shown to be rotation invariant. We show that, using a hybrid data mining technique, the algorithm can be used for rotation invariant content based image retrieval (CBIR). The proposed rotation invariant retrieval algorithm, suitable for both texture and nontexture images, avoids missing any relevant images but may retrieve some other images which are not very relevant. We show that the higher precision can however be achieved by pruning out irrelevant images. (C) 2004 Elsevier B.V. All rights reserved.

Keywords:

content based retrieval

radial symmetry

rotation invariance and wavelets

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