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   -> Volume 7, Issue 1


Thesis: Filter and Filter Bank Design for Image Texture Recognition
 
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Trygve Randen (t.randen@ieee.org)
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PostPosted: Mon Jan 12, 1998 3:40 pm    
Subject: Thesis: Filter and Filter Bank Design for Image Texture Recognition
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#9 Thesis: Filter and Filter Bank Design for Image Texture Recognition

Dr.Ing. dissertation:
Filter and Filter Bank Design for Image Texture Recognition
by Trygve Randen

Abstract

The focus of this dissertation is on the design of two-dimensional
filters for feature extraction, segmentation, and classification of
digital images with textural content. The features are extracted by
filtering with a linear filter and estimating the local energy of the
filter response. The dissertation gives a review covering broadly
most previous approaches to texture feature extraction and continues
with proposals of several new techniques. Texture feature extraction
using a quadrature mirror filter (QMF) bank is proposed, utilizing
both critically sampled and full rate implementations. In the
critically sampled case, tremendous computational savings can be
realized. One of the major conclusions of the experiments is that it
is possible to use sub-sampled filters with only a modest degradation
in segmentation accuracy -- realizing considerable computational
savings. Furthermore, the commonly used octave band decomposition is
evaluated against alternative decompositions, concluding that
non-octave decompositions are generally superior. The QMF filter bank
features are tested on benchmark images, on document segmentation, and
on image content search.

Advisor: Prof. John H=E5kon Hus=F8y, Stavanger College, Stavanger,
Norway (jonh@hsr.no) Granting institution: Norwegian University of
Science and Technology, Trondheim, Norway

The work was performed at Stavanger College, Stavanger, Norway
Acceptance date (defense date): November 24, 1997

Information:
Trygve Randen Schlumberger Geco-Prakla P.O. Box 330 4001 Stavanger
Norway E-mail: t.randen@ieee.org URL: http://www.hsr.no/~tranden/

Committee:
Prof. Anil K. Jain, Michigan State University, East Lansing,
MI, USA (jain@cps.msu.edu)
Dr. Lars Lundheim, SINTEF, Trondheim, Norway
(Lars.Lundheim@informatics.sintef.no)
Prof. Sven Ole Aase, Stavanger College, Stavanger, Norway
(aase@hsr.no)
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