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Using Wavelet Extraction for Haptic Texture Classification

Adi, Waskito and Sulaiman, Suziah (2009) Using Wavelet Extraction for Haptic Texture Classification. In: Lecture Notes in Computer Science. Springer-Verlag, pp. 314-325.

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Abstract

While visual texture classification is a widely-researched 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.

Item Type:Book Section
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Academic Subject Two:Geosciences
Departments / MOR / COE:Departments > Computer Information Sciences
ID Code:2002
Deposited By: Dr Suziah Sulaiman
Deposited On:10 May 2010 10:47
Last Modified:20 Mar 2017 08:11

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