An efficient method for image mining using GLCM and neural network

  • Authors

    • T R. Nisha Dayana
    • Dr A. Lenin Fred
    2018-06-08
    https://doi.org/10.14419/ijet.v7i2.33.13859
  • GLCM (Gray Level Co-Occurrence Matrix) Feature, CBIR (Content Based Image Retrieval), ANN (Artificial Neural Network), ABC (Artificial Bee Colony).

  • Abstract

    Currently, content-based Image recovery (CBIR) drives for producing approaches which supports viable searching and scanning of vast picture progressive libraries by considering unwavering image texture features and has been a rapidly growing inspection bearing among image information recovery, computer vision, and database. The learning procedure of CBIR is achieved with the Neural Network method together with GLCM feature abstraction in our projected technique. Furthermore, with the ABC algorithm the normal/abnormal arrangement of the medical dataset images is managed. Lastly, to regulate the function of the projected method the solutions were replicated and associated with the available method. In the working platform of MATLAB, the projected method is applied.

     

     

  • References

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  • How to Cite

    R. Nisha Dayana, T., & A. Lenin Fred, D. (2018). An efficient method for image mining using GLCM and neural network. International Journal of Engineering & Technology, 7(2.33), 76-83. https://doi.org/10.14419/ijet.v7i2.33.13859

    Received date: 2018-06-08

    Accepted date: 2018-06-08

    Published date: 2018-06-08