Authors :
G.M.K.B. Karunasena; H.D.N.S. Priyankara; B.G.D.A. Madushanka
Volume/Issue :
Volume 5 - 2020, Issue 6 - June
Google Scholar :
http://bitly.ws/9nMw
Scribd :
https://bit.ly/3iDACxH
DOI :
10.38124/IJISRT20JUN691
Abstract :
Rice grain quality inspection is a major
process in rice production. To provide quality and
accurate results in rice grain analyzing it is important to
analyze rice grains one by one in a testing sample. In the
current situation, most of rice grain producers inspect
rice grains manually without using any automated
process. The major problem is the accuracy of testing
results depends on human quality because manually
processes include human errors. The manual inspection
of rice grains is a very complicated and time-consuming
process due to these reasons most of the inspector's
effect by external factors such as fatigue, tension etc. In
this research, we provide a time-efficient and low-cost
solution for reducing above-mentioned limitations by
developing software. It uses modern image processing to
analyze rice grains one by one efficiently over the
manual examination. The quality of rice samples can be
determined with the help of colour, and geometric
features such as area, maximum length, maximum
width and aspect ratio. This analyzing system designed
and developed for measure area, maximum length,
maximum width and aspect ratio by using Java
programming language, morphological and colour
operations in computer vision and finally the accuracy
of the system tested by comparing manually tested
sample and results from the system. According to the
results, it shows this system provides more than 85
percent accuracy with confirming this was a better
solution
Keywords :
Image Processing, Rice Grain Quality, Morphological Operations, Java For Image Processing, Rice Grading
Rice grain quality inspection is a major
process in rice production. To provide quality and
accurate results in rice grain analyzing it is important to
analyze rice grains one by one in a testing sample. In the
current situation, most of rice grain producers inspect
rice grains manually without using any automated
process. The major problem is the accuracy of testing
results depends on human quality because manually
processes include human errors. The manual inspection
of rice grains is a very complicated and time-consuming
process due to these reasons most of the inspector's
effect by external factors such as fatigue, tension etc. In
this research, we provide a time-efficient and low-cost
solution for reducing above-mentioned limitations by
developing software. It uses modern image processing to
analyze rice grains one by one efficiently over the
manual examination. The quality of rice samples can be
determined with the help of colour, and geometric
features such as area, maximum length, maximum
width and aspect ratio. This analyzing system designed
and developed for measure area, maximum length,
maximum width and aspect ratio by using Java
programming language, morphological and colour
operations in computer vision and finally the accuracy
of the system tested by comparing manually tested
sample and results from the system. According to the
results, it shows this system provides more than 85
percent accuracy with confirming this was a better
solution
Keywords :
Image Processing, Rice Grain Quality, Morphological Operations, Java For Image Processing, Rice Grading
