Abstract
Since more than 50 years texture in image material is a topic of research. Hereby, color was ignored mostly. This study compares 70 different configurations for texture analysis, using four features. For the configurations we used: (i) a gray value texture descriptor: the co-occurrence matrix and a color texture descriptor: the color correlogram, (ii) six color spaces, and (iii) several quantization schemes. A three classifier combination was used to classify the output of the configurations on the VisTex texture database. The results indicate that the use of a coarse HSV color space quantization can substantially improve texture recognition compared to various other gray and color quantization schemes.
Original language | Undefined |
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Pages | 35-42 |
Number of pages | 8 |
Publication status | Published - 21 Oct 2004 |
Event | 16th Belgium-Dutch Conference on Artificial Intelligence, BNAIC 2004 - Groningen, Netherlands Duration: 21 Oct 2004 → 22 Oct 2004 Conference number: 16 |
Conference
Conference | 16th Belgium-Dutch Conference on Artificial Intelligence, BNAIC 2004 |
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Abbreviated title | BNAIC |
Country/Territory | Netherlands |
City | Groningen |
Period | 21/10/04 → 22/10/04 |
Keywords
- HMI-VRG: Virtual Reality and Graphics
- Texture
- Pattern Recognition
- co-occurence matrix
- color correlogram
- Color
- HMI-CI: Computational Intelligence
- HMI-HF: Human Factors
- IR-79317
- Classification
- Evaluation
- EWI-21117