Texture recognition under scale and illumination variations
ABSTRACTVisual scene recognition is predominantly based on visual textures representing an object's material properties. However, the single material texture varies in scale and illumination angles due to mapping an object's shape. We present a comparative study of the colour histogram, Ga...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2024-01-01
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| Series: | Journal of Information and Telecommunication |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/24751839.2023.2265190 |
| Summary: | ABSTRACTVisual scene recognition is predominantly based on visual textures representing an object's material properties. However, the single material texture varies in scale and illumination angles due to mapping an object's shape. We present a comparative study of the colour histogram, Gabor, opponent Gabor, Local Binary Pattern (LBP), and wide-sense Markovian textural features concerning their sensitivity to simultaneous scale and illumination variations. Due to their application dominance, these textural features are selected from more than 50 published textural features. Markovian features are information preserving, and we demonstrate their superior performance for scale and illumination variable observation conditions over the standard alternative textural features. We bound the scale variation by double size, and illumination variation includes illumination spectra, acquisition devices, and 35 illumination directions spanned above a sample hemisphere. Recognition accuracy is tested on textile patterns from the University of East Anglia and wood veneers from UTIA BTF databases. |
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| ISSN: | 2475-1839 2475-1847 |