Using Wavelet Extraction for Haptic Texture Classification
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 clas...
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| Other Authors: | |
| Format: | Book Section |
| Language: | English |
| Published: |
Springer-Verlag
2009
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| Subjects: | |
| Online Access: | http://scholars.utp.edu.my/id/eprint/2002/ http://scholars.utp.edu.my/id/eprint/2002/1/IVIC_PID27_sentToPGOffice_latest.pdf |
| _version_ | 1848659193778667520 |
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| author | Adi, Waskito Sulaiman, Suziah |
| author2 | Badioze Zaman, Halimah |
| author_facet | Badioze Zaman, Halimah Adi, Waskito Sulaiman, Suziah |
| author_sort | Adi, Waskito |
| building | UTP Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-13T07:26:32Z |
| format | Book Section |
| id | oai:scholars.utp.edu.my:2002 |
| institution | Universiti Teknologi Petronas |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-13T07:26:32Z |
| publishDate | 2009 |
| publisher | Springer-Verlag |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | oai:scholars.utp.edu.my:20022017-03-20T08:11:55Z http://scholars.utp.edu.my/id/eprint/2002/ Using Wavelet Extraction for Haptic Texture Classification Adi, Waskito Sulaiman, Suziah QA75 Electronic computers. Computer science 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. Springer-Verlag Badioze Zaman, Halimah Robinson, Peter Petrou, Maria Olivier, Patrick Schroder, Heiko Shih, Timothy 2009-11 Book Section PeerReviewed application/pdf en http://scholars.utp.edu.my/id/eprint/2002/1/IVIC_PID27_sentToPGOffice_latest.pdf Adi, Waskito and Sulaiman, Suziah (2009) Using Wavelet Extraction for Haptic Texture Classification. In: Lecture Notes in Computer Science. Springer-Verlag, pp. 314-325. |
| spellingShingle | QA75 Electronic computers. Computer science Adi, Waskito Sulaiman, Suziah Using Wavelet Extraction for Haptic Texture Classification |
| title | Using Wavelet Extraction for Haptic Texture
Classification |
| title_full | Using Wavelet Extraction for Haptic Texture
Classification |
| title_fullStr | Using Wavelet Extraction for Haptic Texture
Classification |
| title_full_unstemmed | Using Wavelet Extraction for Haptic Texture
Classification |
| title_short | Using Wavelet Extraction for Haptic Texture
Classification |
| title_sort | using wavelet extraction for haptic texture
classification |
| topic | QA75 Electronic computers. Computer science |
| url | http://scholars.utp.edu.my/id/eprint/2002/ http://scholars.utp.edu.my/id/eprint/2002/1/IVIC_PID27_sentToPGOffice_latest.pdf |