Texture classification using Steerable Pyramid based Laws’ Masks
This paper progress towards a new feature extraction technique by combining the two existing methods named as Laws’ mask and steerable pyramid for texture classification. Texture parameters are derived and classified for accepted Laws’ mask method. In this paper texture features are extracted and cl...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2017-05-01
|
| Series: | Journal of Electrical Systems and Information Technology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2314717216300721 |
| _version_ | 1818617110512795648 |
|---|---|
| author | Sonali Dash Uma Ranjan Jena |
| author_facet | Sonali Dash Uma Ranjan Jena |
| author_sort | Sonali Dash |
| collection | DOAJ |
| description | This paper progress towards a new feature extraction technique by combining the two existing methods named as Laws’ mask and steerable pyramid for texture classification. Texture parameters are derived and classified for accepted Laws’ mask method. In this paper texture features are extracted and classified using new approaches, which are carried out by integrating both steerable pyramid and Laws’ mask (SPLM) methods. The comparison of the methods yields that the Steerable Pyramid based Laws’ Mask (SPLM) texture feature extraction technique using fifth level of image decomposition level resulted in the best classification accuracy. We use simple k-NN classifier for classification purpose. Our proposed approaches are tested on Brodatz database. Experimental results on fused features established the combination of two feature sets always outperform the conventional Laws’ mask method. |
| first_indexed | 2024-12-16T17:00:29Z |
| format | Article |
| id | doaj.art-ba12e721436c473cbf38c2249c6501d2 |
| institution | Directory Open Access Journal |
| issn | 2314-7172 |
| language | English |
| last_indexed | 2024-12-16T17:00:29Z |
| publishDate | 2017-05-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Journal of Electrical Systems and Information Technology |
| spelling | doaj.art-ba12e721436c473cbf38c2249c6501d22022-12-21T22:23:45ZengSpringerOpenJournal of Electrical Systems and Information Technology2314-71722017-05-014118519710.1016/j.jesit.2016.10.001Texture classification using Steerable Pyramid based Laws’ MasksSonali DashUma Ranjan JenaThis paper progress towards a new feature extraction technique by combining the two existing methods named as Laws’ mask and steerable pyramid for texture classification. Texture parameters are derived and classified for accepted Laws’ mask method. In this paper texture features are extracted and classified using new approaches, which are carried out by integrating both steerable pyramid and Laws’ mask (SPLM) methods. The comparison of the methods yields that the Steerable Pyramid based Laws’ Mask (SPLM) texture feature extraction technique using fifth level of image decomposition level resulted in the best classification accuracy. We use simple k-NN classifier for classification purpose. Our proposed approaches are tested on Brodatz database. Experimental results on fused features established the combination of two feature sets always outperform the conventional Laws’ mask method.http://www.sciencedirect.com/science/article/pii/S2314717216300721Steerable pyramidLaws’ maskFeature extractionTexture classification |
| spellingShingle | Sonali Dash Uma Ranjan Jena Texture classification using Steerable Pyramid based Laws’ Masks Journal of Electrical Systems and Information Technology Steerable pyramid Laws’ mask Feature extraction Texture classification |
| title | Texture classification using Steerable Pyramid based Laws’ Masks |
| title_full | Texture classification using Steerable Pyramid based Laws’ Masks |
| title_fullStr | Texture classification using Steerable Pyramid based Laws’ Masks |
| title_full_unstemmed | Texture classification using Steerable Pyramid based Laws’ Masks |
| title_short | Texture classification using Steerable Pyramid based Laws’ Masks |
| title_sort | texture classification using steerable pyramid based laws masks |
| topic | Steerable pyramid Laws’ mask Feature extraction Texture classification |
| url | http://www.sciencedirect.com/science/article/pii/S2314717216300721 |
| work_keys_str_mv | AT sonalidash textureclassificationusingsteerablepyramidbasedlawsmasks AT umaranjanjena textureclassificationusingsteerablepyramidbasedlawsmasks |