Rajpoot, Nasir M. (Nasir Mahmood) (2003) Local discriminant wavelet packet basis for texture classification. In: Wavelets - Applications in Signal and Image Processing X Conference, San Diego, CA, 04-08 Aug 2003. Published in: Wavelets: Applications in Signal and Image Processing X. SPIE Proceedings, Volume 5207 (Part 1 & 2). pp. 774-783. ISBN 0819450804. ISSN 0277-786X.

Preview

PDF WRAP_Rajpoot_waveletsX03.pdf - Accepted Version - Requires a PDF viewer. Download (562Kb) | Preview

Request Changes to record.

Abstract

Wavelet packets are well-known for their ability to compactly represent textures consiting of oscillatory patterns such as fingerprints or striped cloth. In this paper, we report recent work on representing both periodic and granular types of texture using adaptive wavelet basis functions. The discrimination power of a wavelet packet subband can be defined as its ability to differentiate between any two texture classes in the transform domain, consequently leading to better classification results. The problem of adaptive wavelet basis selection for texture analysis can, therefore, be solved by using a dynamic programming approach to find the best basis from a library of orthonormal basis functions with respect to a discriminant measure. We present a basis selection algorithm which extends the concept of 'Local Discrminant Basis' (Saito and Coifman, 1994) to two dimensions. The problem of feature selection is addressed by sorting the features according to their relevance as described by the discriminant measure, which has a significant advantage over other feature selection methods that both basis selection and reduction of dimensionality of the feature space can be done simultaneously. We show that wavelet packets are good at representing not only oscillatory patterns but also granular textures. Comparative results are presented for four different distance metrics: Kullback-Leibler (KL) divergence, Jensen-Shannon (JS) divergence, Euclidean distance, and Hellinger distance. Initial experimental results show that Hellinger and Euclidean distance metrics may perform better as compared to other cost functions.

Item Type:	Conference Item (Paper)
Subjects:	Q Science > QC Physics
Divisions:	Faculty of Science, Engineering and Medicine > Science > Computer Science
Series Name:	PROCEEDINGS OF THE SOCIETY OF PHOTO-OPTICAL INSTRUMENTATION ENGINEERS (SPIE)
Journal or Publication Title:	Wavelets: Applications in Signal and Image Processing X. SPIE Proceedings
Publisher:	SPIE -int society optical engineering
ISBN:	0819450804
ISSN:	0277-786X
Editor:	Unser, MA and Aldroubi, A and Laine, AF
Official Date:	13 November 2003
Dates:	Date Event 13 November 2003 Published
Volume:	Volume 5207
Number:	Part 1 & 2
Number of Pages:	10
Page Range:	pp. 774-783
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Restricted or Subscription Access
Date of first compliant deposit:	4 December 2015
Date of first compliant Open Access:	4 December 2015
Conference Paper Type:	Paper
Title of Event:	Wavelets - Applications in Signal and Image Processing X Conference
Type of Event:	Conference
Location of Event:	San Diego, CA
Date(s) of Event:	04-08 Aug 2003

Data sourced from Thomson Reuters' Web of Knowledge

Request changes or add full text files to a record

Repository staff actions (login required)

View Item

Downloads