Abstract
Recently the use of Hermite functions in vision and image analysis has gained interest in the image processing community. Hermite functions are related to Gaussian functions through a differential operator. In the search for a suitable spatially localized, but not-redundant, alternative to the Gabor approach, Gaussian derivatives as basis functions were introduced. The literature reports that Hermite functions fit the profiles of many cells in the striate cortex very well. We will present some results on texture analysis using Hermite functions.
This research was supported by the USAF Armstrong Laboratory, Williams AFB, Arizona and USAF Contract F33615-90-C-0005 to the University of Dayton Research Institute. All the authors would like to thank Professor Norman Zabusky, head of the Visualization and Quantification Laboratory at Rutgers University, for supporting this project. We also thank Mr. Y. Tan and A. Feher for software support.
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Gertner, I., Geri, G.A., Pierce, B. (1994). Texture analysis with Hermite basic elementary functions. In: Byrnes, J.S., Byrnes, J.L., Hargreaves, K.A., Berry, K. (eds) Wavelets and Their Applications. NATO ASI Series, vol 442. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-1028-0_19
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