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Texture Analysis for Rice Grain Classification Using Wavelet Decomposition and Back Propagation Neural Network

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Book cover Intelligent Techniques and Applications in Science and Technology (ICIMSAT 2019)

Part of the book series: Learning and Analytics in Intelligent Systems ((LAIS,volume 12))

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Abstract

This paper deals with the classification of eight types of rice grain using image processing and neural network. Three different texture feature extraction schemes based on co-occurrence matrix, run length matrix and wavelet decomposition were considered. The contribution of these texture feature extraction techniques towards rice grain classification were analysed and compared. A back propagation neural network is used for this classification task. The performance in terms of classification accuracy of the above three texture feature extraction schemes where tested. It is found that texture feature based on wavelet decomposition is able to classify eight different types of rice grain with an overall classification accuracy of 98.87% as compared to other texture feature extraction schemes discussed in this paper.

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Authors and Affiliations

  1. Electrical Engineering Department, Mizoram University, Aizawl, 796004, India

    Ksh. Robert Singh

  2. Electrical Engineering Department, National Institute of Technology Silchar, Silchar, 708810, India

    Saurabh Chaudhury

Authors
  1. Ksh. Robert Singh
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  2. Saurabh Chaudhury
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Corresponding author

Correspondence to Ksh. Robert Singh .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, Siliguri Institute of Technology, Sukna, West Bengal, India

    Subhojit Dawn

  2. Department of Automation and Applied Informatics, Aurel Vlaicu University of Arad, Arad, Arad, Romania

    Valentina Emilia Balas

  3. Department of Psychology and IIASS, Università della Campania “Luigi Vanvitelli”, Caserta, Caserta, Italy

    Anna Esposito

  4. Mizoram University, Aizawl, Mizoram, India

    Sadhan Gope

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Singh, K.R., Chaudhury, S. (2020). Texture Analysis for Rice Grain Classification Using Wavelet Decomposition and Back Propagation Neural Network. In: Dawn, S., Balas, V., Esposito, A., Gope, S. (eds) Intelligent Techniques and Applications in Science and Technology. ICIMSAT 2019. Learning and Analytics in Intelligent Systems, vol 12. Springer, Cham. https://doi.org/10.1007/978-3-030-42363-6_7

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