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Colour discernment of tomatoes using machine vision system with OpenCV Python and Raspberry Pi

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Title Colour discernment of tomatoes using machine vision system with OpenCV Python and Raspberry Pi
 
Creator Joice, A Astina
Rajkumar, P
Deepa, J
Arulmari, R
 
Subject Image evaluation
Machine Vision
Programming code
Raspberry Pi
Sorting
 
Description 502-508
Colour is the first quality attribute of food that consumers examine and it is an important component of food quality that
influences market acceptance. Classification of fruits by visual inspection is an arduous, time-consuming process and prone
to human error. The machine vision system is a distributed control system that integrates several machine vision modules
with a control module and a user interface unit. This research proposes a method for recognising and sorting tomato fruits
into a preferred location continuously. Before designing colour sorter the physical properties of fruits were studied. The
major and minor diameter of the tomatoes ranges from 45-60mm and 35-50mm, respectively. The mean geometric diameter,
sphericity and surface area were 48.64mm,0.94 and 6477.14mm2 respectively. The average length, width, thickness, bulk
density and true density were 54.63mm, 48.44mm, 51.42mm, 0.6874g/cm3, 0.9852g/cm3, respectively. The colour sorter
was researched, designed and created with Raspberry Pi, USB camera, servo motor and different digital as well as
mechanical components. The model used for Raspberry Pi is Raspberry Pi 3 Model B+, USB camera with a video resolution
of 640 x 480, 4.2-6V servo motor. Image evaluation is completed on each captured picture and Raspberry Pi will do the
selection of which fruit can be sorted. Specific programming code in Python is written for this system. The developed colour
sorter captures images and diverts fruits into the respective channel at the rate of 1800 fruits/h (i.e.one fruit per 2 seconds).
 
Date 2022-08-16T04:47:15Z
2022-08-16T04:47:15Z
2022-08
 
Type Article
 
Identifier 0975-1017 (Online); 0971-4588 (Print)
http://nopr.niscpr.res.in/handle/123456789/60280
https://doi.org/10.56042/ijems.v29i4.55059
 
Language en
 
Publisher NIScPR-CSIR,India
 
Source IJEMS Vol.29(4) [AUG 2022]