Authorís Marcin Kociolek,
National Institute of Standards and Technology
Manufacturing Systems Integration Division (826)
Design Processing Group
office: Metrology (220), Room A122
address: 100 Bureau Drive, Stop 8263
:† Gaithersburg, MD 20899-8263
phone: (+1 301) 975-5994
fax: (+1 301) 975-4482
Mentor: Ram D. Sriram (301) 975-3507
I am not a Sigma Xi member
DIGITAL IMAGE TEXTURE CLASSIFICATION BY MEANS OF MODIFIED 2D DISCRETE WAVELET TRANSFORM DERIVED FEATURES
Although there is no strict definition of the image texture, it is easily perceived by humans and is believed to be a rich source of visual information Ė about the nature and threedimensional shape of physical objects . Generally speaking, textures are complex visual patterns composed of entities, or subpatterns, that have characteristic brightness, colour, slope, size, etc. Thus texture can be regarded as a similarity grouping in an image The local subpattern properties give rise to the perceived lightness, uniformity, density, roughness, regularity, linearity, frequency, phase, directionality, coarseness, randomness, fineness, smoothness, granulation, etc., of the texture as a whole. There are four major issues in texture analysis:
Feature extraction is the first stage of image texture analysis. Results obtained from this stage are used for texture discrimination, texture classification or object shape determination.
This poster presents application of modified 2D discrete wavelet transform derived features for digital image texture classification. During the described research, software for computation of proposed features has been developed. Described texture classification method was tested on Brodatz texture sets. The robustness of the proposed method of texture classification was demonstrated.
This work summarizes Authorís self researches, leaded in years 2004,2005 in the Institute of Electronics, Technical University of Lodz.
 A. Materka, M. Strzelecki: Texture Analysis Methods - A Review; http://www.eletel.p.lodz.pl/cost/publikacje.html