Abstract
This paper presents a new method for rotation invariant texture classification based on the circular Gabor wavelets. A circular Gabor filter bank is proposed to decompose an image into multiple scales and be rotation invariant. By the mean and variance of the circular Gabor filtered image, a discriminant can be found to classify rotated images. In the primary experiments, comparatively high correct classification rates were obtained using a large test sample set.
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© 2007 Springer Berlin Heidelberg
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Yin, Q., Kim, J.N. (2007). Rotation Invariant Texture Classification Using Circular Gabor Filter Banks. In: Shi, Y., van Albada, G.D., Dongarra, J., Sloot, P.M.A. (eds) Computational Science – ICCS 2007. ICCS 2007. Lecture Notes in Computer Science, vol 4489. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72588-6_25
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DOI: https://doi.org/10.1007/978-3-540-72588-6_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72587-9
Online ISBN: 978-3-540-72588-6
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