Abstract
Granular computing as an enabling technology and as such it cuts across a broad spectrum of disciplines and becomes important to many areas of applications. In this paper, we present our model of information granulation that is more suitable to image recognition. Then, we construct an image granule framework and present a granulation based image texture recognition algorithm. We compare our algorithm with some other algorithms and the results show that our algorithm is effective and efficient.
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Hu, H., Zheng, Z., Shi, Z.P., Li, Q.Y., Shi, Z.Z.: Texture classification using multi-scale rough module_matching and module_selection (to appear)
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© 2004 Springer-Verlag Berlin Heidelberg
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Zheng, Z., Hu, H., Shi, Z. (2004). Granulation Based Image Texture Recognition. In: Tsumoto, S., Słowiński, R., Komorowski, J., Grzymała-Busse, J.W. (eds) Rough Sets and Current Trends in Computing. RSCTC 2004. Lecture Notes in Computer Science(), vol 3066. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25929-9_82
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DOI: https://doi.org/10.1007/978-3-540-25929-9_82
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22117-3
Online ISBN: 978-3-540-25929-9
eBook Packages: Springer Book Archive