A wavelet based multiresolution algorithm for rotation invariant feature extraction Ch.S. Sastry, Arun K. Pujari * , B.L. Deekshatulu, C. Bhagvati Artificial Intelligence Lab, Department of Computer and Information Sciences, University of Hyderabad, Hyderabad 500046, India Received 11 December 2003; received in revised form 25 May 2004 Available online 16 September 2004 Abstract 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. Ó 2004 Elsevier B.V. All rights reserved. Keywords: Content based retrieval; Radial symmetry; Rotation invariance and wavelets 1. Introduction Inthepastdecade,withtherapidincreaseinthe use of internet, steady growth of computer power, the demand for storing multimedia information has increased tremendously. Therefore, efficient andfastmethodsareneededtoretrievedesiredim- age from large databases. Traditionally, text annotations, such as file name, caption, key words etc, have been used to describe the contents of images. These textual annotations become the basis for indexing and searching using the mature text search algorithms. Asthesealgorithmsaretobeappliedtolargedata- bases, the use of annotations becomes not only cumbersome but also inadequate to represent the image content. Many content based image retrie- val (CBIR) algorithms are proposed in the current 0167-8655/$ - see front matter Ó 2004 Elsevier B.V. All rights reserved. doi:10.1016/j.patrec.2004.07.011 * Corresponding author. Tel.: +91 40 23010500; fax: +91 40 23010780. E-mail addresses: s.challa@lycos.com (Ch.S. Sastry), ak- pcs@uohyd.ernet.in (A.K. Pujari), bldcs@uohyd.ernet.in (B.L. Deekshatulu), chakcs@uohyd.ernet.in (C. Bhagvati). Pattern Recognition Letters 25 (2004) 1845–1855 www.elsevier.com/locate/patrec