Answers are grounded in this paper and cite their sources.
Bananas have different nutritional content at each level of ripeness. Therefore, choosing a banana with the right level of ripeness is necessary in order to obtain fruit according to our needs. This paper conducted a review of the non-destructive identification of banana ripeness using banana fruit imagery and computer vision method. Through the review literature, this paper is presented in a concise and detailed manner related to the type of image used and the stages of the identification process starting from feature extraction, reduction of dimension and feature selection, and classification. The result of the review showed a considerable potential for the use of digital imagery and computer vision method in the automatically identifying of banana ripeness.
No takes yet. Share an insight, caveat, or question.
Dewi et al. (2021) studied this question.