Abstract
In the context of texture classification, this article explores the capacity and the performance of some combinations of feature extraction, linear and nonlinear dimensionality reduction techniques and several kinds of classification methods. The performances are evaluated and compared in term of classification error. In order to test our texture classification protocol, the experiment carried out images from two different sources, the well known Brodatz database and our leaf texture images database.
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Journaux, L., Destain, MF., Miteran, J., Piron, A., Cointault, F. (2008). Texture Classification with Generalized Fourier Descriptors in Dimensionality Reduction Context: An Overview Exploration. In: Prevost, L., Marinai, S., Schwenker, F. (eds) Artificial Neural Networks in Pattern Recognition. ANNPR 2008. Lecture Notes in Computer Science(), vol 5064. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69939-2_27
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DOI: https://doi.org/10.1007/978-3-540-69939-2_27
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