Article | KEER2014. Proceedings of the 5th Kanesi Engineering and Emotion Research; International Conference; Linköping; Sweden; June 11-13 | Texture Image Classification Using Extended 2D HLAC Features Link�ping University Electronic Press Conference Proceedings
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Title:
Texture Image Classification Using Extended 2D HLAC Features
Author:
Motofumi Suzuki: The Open University of Japan, Japan
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Full text (pdf)
Year:
2014
Conference:
KEER2014. Proceedings of the 5th Kanesi Engineering and Emotion Research; International Conference; Linköping; Sweden; June 11-13
Issue:
100
Article no.:
091
Pages:
1093-1102
No. of pages:
10
Publication type:
Abstract and Fulltext
Published:
2014-06-11
ISBN:
978-91-7519-276-5
Series:
Linköping Electronic Conference Proceedings
ISSN (print):
1650-3686
ISSN (online):
1650-3740
Publisher:
Linköping University Electronic Press; Linköpings universitet


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HLAC (Higher Order Local Autocorrelation) features are popular image descriptors that have been used for various image-processing applications since the 1980s. Examples of the application of the HLAC features include KANSEI retrievals and subjective retrievals of 2D image databases. In this paper; standard HLAC masks are extended for computing a massive number of features. Typical HLAC features are computed by applying 25 masks to a binary image; whereas our Ext-HLAC features are computed by applying 16;241;567 masks. Since there are a high number of mask combinations; we have developed Ext-HLAC mask generation software programs. Ext-HLAC masks were tested by using 2D benchmark image database sets. For each image; the pattern features were extracted by applying Ext-HLAC masks; and the pattern features were analyzed by a k-NN based approach. Our preliminary experiments show high classification rates for certain image databases.

Keywords: HLAC; Ext-HLAC; pattern feature; k-NN; image classification

KEER2014. Proceedings of the 5th Kanesi Engineering and Emotion Research; International Conference; Linköping; Sweden; June 11-13

Author:
Motofumi Suzuki
Title:
Texture Image Classification Using Extended 2D HLAC Features
References:

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Suzuki; M.T.; Yaginuma; Y.; Yamada; T.; & Shimizu; Y.; (2006). Shape Descriptors based on Extended 3D Higher Order Local Autocorrelation Masks; 2006 IEEE Mountain Workshop on Adaptive and Learning Systems (SMCals 2006); (pp138-143).

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KEER2014. Proceedings of the 5th Kanesi Engineering and Emotion Research; International Conference; Linköping; Sweden; June 11-13

Author:
Motofumi Suzuki
Title:
Texture Image Classification Using Extended 2D HLAC Features
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