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.
|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||16th Belgium-Dutch Conference on Artificial Intelligence, BNAIC 2004|
|Period||21/10/04 → 22/10/04|
- HMI-VRG: Virtual Reality and Graphics
- Pattern Recognition
- co-occurence matrix
- color correlogram
- HMI-CI: Computational Intelligence
- HMI-HF: Human Factors
Verbrugge, R. (Ed.), van den Broek, E., van Rikxoort, E. M., Taatgen, N. (Ed.), & Schomaker, L. (Ed.) (2004). Evaluation of color representation for texture analysis. 35-42. Paper presented at 16th Belgium-Dutch Conference on Artificial Intelligence, BNAIC 2004, Groningen, Netherlands.