The Generalized Gabor Scheme of Image Representation in Biological and Machine Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multichannel Texture Analysis Using Localized Spatial Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image representation and compression with steered Hermite transforms
Signal Processing
Filtering for Texture Classification: A Comparative Study
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Parametric Texture Model Based on Joint Statistics of Complex Wavelet Coefficients
International Journal of Computer Vision - Special issue on statistical and computational theories of vision: modeling, learning, sampling and computing, Part I
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We present a texture analysis approach for texture image indexing based on Gabor-like Hermite filters, which are steered versions of discrete Hermite filters. Hermite filters are the backbone of the Hermite transform, which is a polynomial transform and a good model of the human visual system. Experimental results show that our filters have better performance than Gabor filters. The texture analysis system is then applied to handwriting document indexing. For that doing, handwriting documents are decomposed into local frequencies through the presented filter bank and, using this decomposition, we analyze the visual aspect of handwritings to compute similarity measures. A direct application is the management of document databases, allowing to find documents coming from the same author or to classify documents containing handwritings that have similar visual aspect. The current results are very promising and show that it is possible to characterize handwritten drawings without any a priori graphemes segmentation.