White whole (WW) grades cashew kernel’s classification using artificial neural network (ANN)

  • Authors

    • Narendra VG Manipal Institute of Technology
    • Dasharathraj K Shetty Manipal Institute of Technology
    2020-02-07
    https://doi.org/10.14419/ijet.v9i1.14878
  • Cashew kernel, Bounding rectangle, Shape features, Artificial Neural Network.

  • Abstract

    In this paper, we introduce an algorithm for the fitting of bounding rectangle to a closed region of cashew kernel in a given image. We propose an algorithm to automatically compute the coordinates of the vertices closed form solution. Which is based on coordinate geometry and uses the boundary points of regions. The algorithm also computes directions of major and minor axis using least-square approach to compute the orientation of the given cashew kernel. More promising results were obtained by extracting shape features of a cashew kernel, it is proved that these features may predominantly use to make the better distinction of cashew kernels of different grades. The intelligent model was designed using Artificial Neural Network (ANN). The model was trained and tested using Back-Propagation learning algorithm and obtained classification accuracy of 89.74%.

     

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  • How to Cite

    VG, N., & K Shetty, D. (2020). White whole (WW) grades cashew kernel’s classification using artificial neural network (ANN). International Journal of Engineering & Technology, 9(1), 187-193. https://doi.org/10.14419/ijet.v9i1.14878

    Received date: 2018-06-30

    Accepted date: 2018-06-30

    Published date: 2020-02-07