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Development of image recognition software based on artificial intelligence algorithm for the efficient sorting of apple fruit

Author

Listed:
  • Ming Yang

    (Recruitment and Employment Office)

  • Pawan Kumar

    (University of Johannesburg)

  • Jyoti Bhola

    (National Institute of Technology)

  • Mohammad Shabaz

    (Chitkara University)

Abstract

Manual sorting of fruits was considered as a significant challenging for agricultural sector as it is a laborious task and may also lead to inconsistency in the classification. In order to improve the apple sorting efficiency and realize the non-destructive testing of apple, the machine vision technology integrated with artificial intelligence was introduced in this article for the design of apple sorting system. This article provides a low budget alternative solution for intelligent grading and sorting of apple fruit employing the deep learning-based approach. The automatic grading of apple was realized according to the determined apple grading standard by applying various stages of artificial intelligence platform like grayscale processing, binarization, enhancement processing, feature extraction and so on. The proposed end-to-end low-cost machine vision system provides an automated sorting of apple and significantly reduces the labor cost and provides a time-effective solution for medium and large-scale enterprises. In order to verify the feasibility of the scheme, the image recognition system of apple sorting machine is tested and the average accuracy of 99.70% is achieved while observing the recognition accuracy 99.38% for the CNN based apple sorting system. The results show that the sorting image recognition system can successfully sort apples according to the perimeter characteristics. It realizes the non-destructive testing and grade classification of apple and provides an important reference value for the research and development of fruit automatic sorting system.

Suggested Citation

  • Ming Yang & Pawan Kumar & Jyoti Bhola & Mohammad Shabaz, 2022. "Development of image recognition software based on artificial intelligence algorithm for the efficient sorting of apple fruit," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 322-330, March.
    • Handle: RePEc:spr:ijsaem:v:13:y:2022:i:1:d:10.1007_s13198-021-01415-1
    DOI: 10.1007/s13198-021-01415-1
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    References listed on IDEAS

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    1. Yang Lu, 2019. "Artificial intelligence: a survey on evolution, models, applications and future trends," Journal of Management Analytics, Taylor & Francis Journals, vol. 6(1), pages 1-29, January.
    2. Yixin Zhou & Ashutosh Sharma & Mehedi Masud & Gurjot Singh Gaba & Gaurav Dhiman & Kayhan Zrar Ghafoor & Mohammed A. AlZain, 2021. "Urban Rain Flood Ecosystem Design Planning and Feasibility Study for the Enrichment of Smart Cities," Sustainability, MDPI, vol. 13(9), pages 1-15, May.
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