基于成熟度分级的芒果图像处理方法

Md. Baig Mohammad, Lakshmi Narayana Thalluri, Renuka Devireddy, Priyanka Ch., Rajiya Sulthana
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引用次数: 2

摘要

食品加工业对我国的发展起着至关重要的作用。芒果是一种营养丰富的经济水果。一般来说,成熟阶段的分类是由人类专家完成的,这是一个艰苦的过程,也是食品加工业的一项具有挑战性的任务。提出了一种成熟阶段分类的机器学习方法。基于MATLAB的实现表明,集成分类器在混淆矩阵、平均准确率、精密度、召回率、特异性和f分等方面优于同类判别分类器。因此,芒果成熟度指数分级对了解芒果的货架期具有十分重要的意义。因此,本文提出了使用机器学习方法对芒果果实进行有效分级的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Image Processing Approach for Grading of Mangoes based on Maturity
Food processing industries plays a vital role for the development of our country. Mango is one of the economical fruit because of its nutrient dense foods. In general, ripening stage classification done by human experts which is strenuous process and a challenging task for food processing industry. A machine learning approach for ripening stage classification has been proposed. A MATLAB based implementation shows that Ensemble classifier outperform their counter parts discriminant classifier in terms confusion matrix, average accuracy, precision, recall, specificity and F-score.So,Maturity index classification of mango plays very important role to get to know about shelf life of mangoes. Thus this paper proposes effective mango fruit grading using machine learning approaches.
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