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A Comparative Study of Texture Measures for Terrain Classification
Abstract
Three standard approaches to automatic texture classification make use of features based on the Fourier power spectrum, on second-order gray level statistics, and on first-order statistics of gray level differences, respectively. Feature sets of these types, all designed analogously, were used to classify two sets of terrain samples. It was found that the Fourier features generally performed more poorly, while the other feature sets all performned comparably.
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Citations
Cited by
A comparative study of texture measures with classification based on featured distributions
Ojala, T., Pietikäinen, M., & Harwood, D. (1996) · Pattern Recognition · doi:10.1016/0031-3203(95)00067-4 · Cited by 6,882
Textural Features Corresponding to Visual Perception
Tamura, H., Mori, S., & Yamawaki, T. (1978) · IEEE Transactions on Systems, Man, and Cybernetics · doi:10.1109/tsmc.1978.4309999 · Cited by 2,155
Markov Random Field Texture Models
Cross, G. R., & Jain, A. K. (1983) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.1983.4767341 · Cited by 1,414
Baraldi, A., & Parmiggiani, F. (1995) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/36.377929 · Cited by 678
(1998) · Cited by 540
Metadata
- Authors
- Weszka, J. S., Dyer, C. R., & Rosenfeld, A.
- Venue
- IEEE Transactions on Systems, Man, and Cybernetics
- Published
- 1976
- Volume
- SMC-6
- Issue
- 4
- Pages
- 269-285
- ISSN
- 0018-9472 (ISSN-L)
- OpenAlex
- W2117395697
- Cited by
- 1,522
- References
- 0
- FWCI
- 85.53
- Type
- journal article
- Language
- en
- Open access
- closed
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- Weszka, J. S., Dyer, C. R., & Rosenfeld, A. (1976). A Comparative Study of Texture Measures for Terrain Classification. IEEE Transactions on Systems, Man, and Cybernetics. https://doi.org/10.1109/tsmc.1976.5408777
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