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Machine vision for automated maturity grading of oil palm fruits : a systematic review

Kamal Afsar, Kamarudin Nur Diyana, Ahmad Khairol Amali Bin, Rahayu Syarifah Bahiyah, Isa Mohd Rizal Mohd, Makhtar Siti Noormiza, Yaakub Zulkifli

Machine Graphics and Vision

2024

Vol. 33, No. 2

47--75

The maturity of oil palm fruits is a very crucial factor for oil extraction industry in Indonesia, Malaysia, Thailand, and other countries to ensure the oil quality and increase productivity. This literature review examines the various machine learning techniques, especially the deep learning techniques used to automate the maturity grading process of oil palm fresh fruit bunches. The crucial advantages of using machine learning approaches were highlighted, and the limitations and prospects of each research article were discussed. This review describes the various image pre-processing techniques utilized to prepare images for model training. CNN is identified as the dominant over all classification techniques of machine learning to classify the oil palm fruits images based on maturity level, due to its ability of learning complex features.