eprintid: 659
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/06/59
datestamp: 2023-11-09 15:48:48
lastmod: 2023-11-09 15:48:48
status_changed: 2023-11-09 15:22:54
type: conference_item
metadata_visibility: show
creators_name: Adi, W.
creators_name: Sulaiman, S.
title: Texture classification using wavelet extraction: An approach to haptic texture searching
ispublished: pub
keywords: Accuracy rate; Energy signatures; Extracting information; Feature vectors; Haptic texture search engine; Haptic textures; Machine learning; Research topics; Sub-bands; Testing data; Texture classification; Texture recognition; Transformation coefficients; Visual texture, Education; Feature extraction; Image analysis; Industrial applications; Information retrieval; Intelligent systems; Robot learning; Search engines; Supervised learning; Textures; World Wide Web, Wavelet decomposition
note: cited By 7; Conference of 2009 Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2009 ; Conference Date: 25 July 2009 Through 26 July 2009; Conference Code:78109
abstract: while visual texture classification is a widely-research topic in image analysis, little is known on its counterpart i.e. the haptic (touch) texture. This paper examines the visual texture classification in order to investigate how well it could be used for haptic texture search engine. In classifying the visual textures, feature extraction for a given image involving wavelet decomposition is used to obtain the transformation coefficients. Feature vectors are formed using energy signature from each wavelet sub-band coefficient. We conducted an experiment to investigate the extent in which wavelet decomposition could be used in haptic texture search engine. The experimental result, based on different testing data, shows that feature extraction using wavelet decomposition achieve accuracy rate more than 96. This demonstrates that wavelet decomposition and energy signature is effective in extracting information from a visual texture. Based on this finding, we discuss on the suitability of wavelet decomposition for haptic texture searching, in terms of extracting information from image and haptic information. © 2009 IEEE.
date: 2009
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-70449126166&doi=10.1109%2fCITISIA.2009.5224167&partnerID=40&md5=bd618445e5126087b513fbd594a15e33
id_number: 10.1109/CITISIA.2009.5224167
full_text_status: none
publication: 2009 Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2009
place_of_pub: Kuala Lumpur
pagerange: 434-439
refereed: TRUE
isbn: 9781424428878
citation:   Adi, W. and Sulaiman, S.  (2009) Texture classification using wavelet extraction: An approach to haptic texture searching.  In: UNSPECIFIED.