Rotationally invariant texture classification

Paul R Hill, David Bull, CN Canagarajah

Research output: Contribution to journalArticle (Academic Journal)peer-review

Abstract

Texture based features used for content based retrieval of images and videos should ideally be invariant to simple transforms such as rotation. This paper introduces the recently developed dual tree complex wavelet transform (DT-CWT) as a tool to extract rotationally invariant texture based features. When applied in two dimensions the DT-CWT produces shift invariant and orientated subbands at each decomposition scale. Rotationally invariant features can be extracted from the energies of these subbands whilst benefiting from the computational efficiency of the decomposition and the ability to choose the transform filters.
Original languageEnglish
Pages (from-to)20/1 - 20/5
JournalIEE Seminar on Time-scale and Time-Frequency Analysis and Applications
DOIs
Publication statusPublished - Feb 2000

Bibliographical note

Sponsorship: This work was supported by the Virtual Centre of Excellence in Digital Broadcast and Multimedia Technology. The authors acknowledge the support and information provided by Dr N.G. Kingsbury of Cambridge
University.

Other identifier: Publ. No. 2000/019
Publisher: Institution of Electrical Engineers (IEE)

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