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Texture Feature Extraction and Classification

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Computer Analysis of Images and Patterns (CAIP 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2124))

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Abstract

This paper describes a novel technique for texture feature extraction and classification. The proposed feature extraction technique uses an Auto-Associative Neural Network (AANN) and the classification technique uses a Multi-Layer Perceptron (MLP) with a single hidden layer. The two approaches such as AANN-MLP and statistical-MLP were investigated. The performance of the proposed techniques was evaluated on large benchmark database of texture patterns. The results are very promising compared to other techniques. Some of the experimental results are presented in this paper.

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© 2001 Springer-Verlag Berlin Heidelberg

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Verma, B., Kulkarni, S. (2001). Texture Feature Extraction and Classification. In: Skarbek, W. (eds) Computer Analysis of Images and Patterns. CAIP 2001. Lecture Notes in Computer Science, vol 2124. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44692-3_28

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  • DOI: https://doi.org/10.1007/3-540-44692-3_28

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42513-7

  • Online ISBN: 978-3-540-44692-7

  • eBook Packages: Springer Book Archive

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