Machine Vision Technique Based Smart Fruit Sorter

• Author(s): A.Gnana Selva Kumar ; Aathisha.S ; Dharani.S ; Revathi.N
• Paper ID: 1701148
• Page: 212-214
• Published Date: 03-05-2019
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 2 Issue 10 April-2019

Abstract

in large scale food production industry, the grading of fruits takes place a major role. In this paper automatic grading of artificial mango is done according to artificial ripening and natural ripening. In terms of texture, shape, size. The proposal scheme work based on Machine Learning technique for grading of mangoes in two different categories, they are natural ripening and artificial ripening. In this system images captured by Raspberry pi V2 camera. Several processing techniques are applied to collect features that required for grading of mangoes. For grading prediction, we are using Convolution Neural Network (CNN) algorithm in Machine learning technique. The proposed system for grading of mango fruit is nearly 92%. Moreover, the repeatability of the proposed system is found to be 100%.

Keywords

CNN algorithm, Machine learning, Raspberry pi

Citations

IRE Journals:
A.Gnana Selva Kumar , Aathisha.S , Dharani.S , Revathi.N "Machine Vision Technique Based Smart Fruit Sorter" Iconic Research And Engineering Journals Volume 2 Issue 10 2019 Page 212-214

IEEE:
A.Gnana Selva Kumar , Aathisha.S , Dharani.S , Revathi.N "Machine Vision Technique Based Smart Fruit Sorter" Iconic Research And Engineering Journals, 2(10)