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Classification of rice seed MR219 and MR269 varieties based on morphological features using machine vision technique

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Bibliographic Details
Main Author: Mohd Shariza Omri, Sabtu
Format: Other
Language:English
Published: Universiti Malaysia Perlis (UniMAP) 2022
Subjects:
Morphological features
Machine vision technique
Rice seed
MR 219
MR 269
Online Access:http://dspace.unimap.edu.my:80/xmlui/handle/123456789/73299
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spelling my.unimap-732992022-01-11T07:45:13Z Classification of rice seed MR219 and MR269 varieties based on morphological features using machine vision technique Mohd Shariza Omri, Sabtu Morphological features Machine vision technique Rice seed MR 219 MR 269 Access is limited to UniMAP community. This project was carried out to classify the morphological features of rice seed varieties of MR219 and MR269 using machine vision technique. The study starts from acquiring image of the rice seed varieties of MR219 and MR269 using a CCD camera. The CCD camera was enclosed in a black box equipped with an illumination system. The images were processed and the morphological features were extracted from the image. This process was carried out in the LabVIEW software. The data was analyzed using MATLAB Neural Network. Through this thesis and data collected, the rice seed varieties can be determined and classified based on the extracted morphological features. The extracted of morphological features were the length, area, width, major axis length, minor axis length, thinness ratio, aspect ratio, rectangular aspect ratio, equivalent diameter, and extend. From the data collected, the lowest MSE which is 2.37592e-1 was acquired using 5 hidden layer of neuron with the highest classification accuracy which is 63.3%. However, the 5 hidden layer of neuron was then tested again to acquire a higher accuracy and the final MSE was 2.09587e-1 with an accuracy of 70%. 2022-01-11T07:45:13Z 2022-01-11T07:45:13Z 2016-06 Other http://dspace.unimap.edu.my:80/xmlui/handle/123456789/73299 en Universiti Malaysia Perlis (UniMAP)
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Morphological features
Machine vision technique
Rice seed
MR 219
MR 269
spellingShingle Morphological features
Machine vision technique
Rice seed
MR 219
MR 269
Mohd Shariza Omri, Sabtu
Classification of rice seed MR219 and MR269 varieties based on morphological features using machine vision technique
description Access is limited to UniMAP community.
format Other
author Mohd Shariza Omri, Sabtu
author_facet Mohd Shariza Omri, Sabtu
author_sort Mohd Shariza Omri, Sabtu
title Classification of rice seed MR219 and MR269 varieties based on morphological features using machine vision technique
title_short Classification of rice seed MR219 and MR269 varieties based on morphological features using machine vision technique
title_full Classification of rice seed MR219 and MR269 varieties based on morphological features using machine vision technique
title_fullStr Classification of rice seed MR219 and MR269 varieties based on morphological features using machine vision technique
title_full_unstemmed Classification of rice seed MR219 and MR269 varieties based on morphological features using machine vision technique
title_sort classification of rice seed mr219 and mr269 varieties based on morphological features using machine vision technique
publisher Universiti Malaysia Perlis (UniMAP)
publishDate 2022
url http://dspace.unimap.edu.my:80/xmlui/handle/123456789/73299
_version_ 1724609977172099072
score 13.222552

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