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An Artificial Intelligence System for Apple Fruit Disease Classification Based on Support Vector Machine and Cockroach Swarm Optimization

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Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2020) (AICV 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1153))

Abstract

This paper presents an artificial intelligent system for detection of apple diseases using Support Vector Machine (SVM) and Cockroach Swarm Optimization (CSO). This paper faces a challenge of content ambiguity. This challenge is mitigated by combining texture classification based on initial k-means clustering. The proposed system is able to extract useful features. There are 4 classes: scab disease, rot disease, blotch disease, and normal. The dataset consists of 320 apple images in total divided into 80 images for each class. SVM is actually a binary classifier. The paper shows how to extend it for multi-class classification. The performance of SVM strongly depends on proper choice of its parameters. CSO meta-heuristic performs fine-tunes for SVM parameters including nonlinear hyper planes, penalty parameter of error term, and degree which is used to find the hyper plane for splitting the data. Results show 94.65% accuracy in detecting the normal apple.

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Author information

Authors and Affiliations

  1. Faculty of Computers and Information, Mansoura University, Mansoura, Egypt

    Mohamed A. El-dosuky

  2. Universidad de Guadalajara CUCEI, Guadalajara, Jalisco, Mexico

    Diego Oliva

  3. Faculty of Computers and Artificial Intelligence, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  4. Scientific research group in Egypt (SRGE), Cairo, Egypt

    Mohamed A. El-dosuky, Diego Oliva & Aboul Ella Hassanien

Authors
  1. Mohamed A. El-dosuky
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  2. Diego Oliva
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  3. Aboul Ella Hassanien
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Corresponding author

Correspondence to Mohamed A. El-dosuky .

Editor information

Editors and Affiliations

  1. Information Technology Department, Cairo University, Faculty of Computers and Information, Giza, Egypt

    Aboul-Ella Hassanien

  2. Faculty of Computers and Information, Benha University, Banha, Egypt

    Ahmad Taher Azar

  3. Faculty of Computers and Information, Suez Canal University, Ismailia, Egypt

    Tarek Gaber

  4. Departamento de Ciencias Computacionales, Universidad de Guadalajara, CUCEI, Guadajalara, Jalisco, Mexico

    Diego Oliva

  5. Faculty of Computer and Information Sciences, Ain Shams University, Cairo, Egypt

    Fahmy M. Tolba

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El-dosuky, M.A., Oliva, D., Hassanien, A.E. (2020). An Artificial Intelligence System for Apple Fruit Disease Classification Based on Support Vector Machine and Cockroach Swarm Optimization. In: Hassanien, AE., Azar, A., Gaber, T., Oliva, D., Tolba, F. (eds) Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2020). AICV 2020. Advances in Intelligent Systems and Computing, vol 1153. Springer, Cham. https://doi.org/10.1007/978-3-030-44289-7_14

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