Abstract
This paper presents a thorough investigation into the use of Gabor filters for the extraction of rotation invariant texture features. Numerous experiments have been conducted to discover the effect of different parameter settings on classification results. The optimum parameter settings are established and tested by classification and content based image retrieval experiments on a large database of randomly rotated Brodatz texture images. Resistance of the method to Gaussian noise is also examined. The issues studied in this paper are of great importance for practical applications but have not been adequately addressed by existing work on texture analysis.
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© 1997 Springer-Verlag Berlin Heidelberg
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Fountain, S.R., Tan, T.N. (1997). Rotation invariant texture features from Gabor filters. In: Chin, R., Pong, TC. (eds) Computer Vision — ACCV'98. ACCV 1998. Lecture Notes in Computer Science, vol 1352. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63931-4_198
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DOI: https://doi.org/10.1007/3-540-63931-4_198
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