A Novel Feature Space for Classifying Textures and Objects in Low-Resolution Infrared Images
This paper reports formation of a novel feature set for classifying textures in low-resolution thermal infrared (TIR) images like the ones acquired during aerial and ground operations of robotic vehicles. The proposed 3-component feature set includes energy coefficients obtained via 3-level overcomp...
| Main Author: | |
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| Format: | Conference Paper |
| Published: |
IEEE
2018
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| Online Access: | http://hdl.handle.net/20.500.11937/74810 |
| _version_ | 1848763378924781568 |
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| author | Khan, Masood Mehmood |
| author_facet | Khan, Masood Mehmood |
| author_sort | Khan, Masood Mehmood |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | This paper reports formation of a novel feature set for classifying textures in low-resolution thermal infrared (TIR) images like the ones acquired during aerial and ground operations of robotic vehicles. The proposed 3-component feature set includes energy coefficients obtained via 3-level overcomplete wavelet decomposition of subimages; three compact statistical descriptors derived from the grey-level co-occurrence matrices of TIR images and; a fractional energy descriptor ?. The energy descriptor ? accounts for emissivity related grey-level variations in the imaged object’s surface. Thus ? would provide succinct information about the influence of the imaged surface characteristics (shape, ambience and tidiness) on grey-level distribution in the image/surface. A fuzzy K-nearest neighbor classifier was used for labelling the image vectors. The reported results show that the proposed feature space would be helpful in classifying textures acquired from a distance under difficult illumination conditions. |
| first_indexed | 2025-11-14T11:02:31Z |
| format | Conference Paper |
| id | curtin-20.500.11937-74810 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T11:02:31Z |
| publishDate | 2018 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-748102019-02-19T04:18:05Z A Novel Feature Space for Classifying Textures and Objects in Low-Resolution Infrared Images Khan, Masood Mehmood This paper reports formation of a novel feature set for classifying textures in low-resolution thermal infrared (TIR) images like the ones acquired during aerial and ground operations of robotic vehicles. The proposed 3-component feature set includes energy coefficients obtained via 3-level overcomplete wavelet decomposition of subimages; three compact statistical descriptors derived from the grey-level co-occurrence matrices of TIR images and; a fractional energy descriptor ?. The energy descriptor ? accounts for emissivity related grey-level variations in the imaged object’s surface. Thus ? would provide succinct information about the influence of the imaged surface characteristics (shape, ambience and tidiness) on grey-level distribution in the image/surface. A fuzzy K-nearest neighbor classifier was used for labelling the image vectors. The reported results show that the proposed feature space would be helpful in classifying textures acquired from a distance under difficult illumination conditions. 2018 Conference Paper http://hdl.handle.net/20.500.11937/74810 IEEE restricted |
| spellingShingle | Khan, Masood Mehmood A Novel Feature Space for Classifying Textures and Objects in Low-Resolution Infrared Images |
| title | A Novel Feature Space for Classifying Textures and Objects in Low-Resolution Infrared Images |
| title_full | A Novel Feature Space for Classifying Textures and Objects in Low-Resolution Infrared Images |
| title_fullStr | A Novel Feature Space for Classifying Textures and Objects in Low-Resolution Infrared Images |
| title_full_unstemmed | A Novel Feature Space for Classifying Textures and Objects in Low-Resolution Infrared Images |
| title_short | A Novel Feature Space for Classifying Textures and Objects in Low-Resolution Infrared Images |
| title_sort | novel feature space for classifying textures and objects in low-resolution infrared images |
| url | http://hdl.handle.net/20.500.11937/74810 |