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@article{160361,
        author = { Shalini M. C. and Dr.Savitha M. and Dr.Bhagya H. K.},
        title = {Detection of Banana Grading Stages Using Image Processing and Machine Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {1},
        pages = {516-519},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=160361},
        abstract = {In order to determine the stages of banana ripening based on colour, the appearance of brown spots, and picture texture data, a computer vision system was put into place. For classification purposes, photos of bananas with their L*, a*, b* values, brown area %, number of brown spots per cm2, homogeneity, contrast, correlation, and entropy of image texture were employed. The results demonstrate that a straightforward classification system can detect the phases of banana ripening just as well as professional visual perception, despite variances in data for colour and appearance. 150 banana samples could be classified with 96% accuracy into the three phases of ripening using the L*, a*, and b* bands, brown area percentage, and contrast. Potential applications of computer vision Online banana ripening stage forecast.},
        keywords = {Banana ripening, computer vision, colour, appearance, categorization},
        month = {},
        }