Abstract
The agriculture sector is a very much potential application domain for computer vision—a major branch of artificial intelligence. Many efforts have been made using different computer vision techniques to address different problems of agriculture. The machine vision-based diagnosis of fruits and vegetables is a notable problem domain in this regard. This problem domain has beckoned the computer vision and machine learning researchers to contribute to this domain. In this chapter, we have performed a comprehensive review on the recent advancement of computer vision and machine learning research efforts for fruit and vegetable disease recognition. Besides, we have given a comparative study on these efforts based on performance metrics to find the state-of-the-art techniques and shows ways for future work. This work is expected to be very much useful for the new and old researchers in the area of machine vision-based fruit and vegetable disease recognition.
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Habib, M.T., Arif, M.A.I., Shorif, S.B., Uddin, M.S., Ahmed, F. (2021). Machine Vision-Based Fruit and Vegetable Disease Recognition: A Review. In: Uddin, M.S., Bansal, J.C. (eds) Computer Vision and Machine Learning in Agriculture. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-33-6424-0_10
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