Classification of cultivated rice Seed MR219 and MR269 varieties based on colour features using machine vision technique
Access is limited to UniMAP community.
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Other |
| Language: | English |
| Published: |
Universiti Malaysia Perlis (UniMAP)
2022
|
| Subjects: | |
| Online Access: | http://dspace.unimap.edu.my:80/xmlui/handle/123456789/74332 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Universiti Malaysia Perlis |
| Language: | English |
| id |
my.unimap-74332 |
|---|---|
| record_format |
dspace |
| spelling |
my.unimap-743322022-02-17T04:03:04Z Classification of cultivated rice Seed MR219 and MR269 varieties based on colour features using machine vision technique Ahmad Yusuf, Hashim School of Bioprocess Engineering Machine vision Rice seed MR219 variety MR269 variety Access is limited to UniMAP community. Final Year Project (FYP) was carried out to extract the colour feature of cultivated rice seed MR219 and MR269 using image analysis. Mostly in rice seed factory, seed inspection need experienced worker to distinguish the quality of the rice seed and the method done was very time consuming. Hence, Machine vision system that consist of couple-charged device (CCD) camera was used in seed testing. The study starts by collecting quality rice seed from the nearby legitimate distributer. This study was focusing on the rice seed type of MR219 and MR269 because these rice seed was often used for rice cultivation throughout Malaysia. Next, the images of MR219 and MR269 was captured using CCD camera. In addition, the study was carried out to create a programming using LabVIEW 2013 to provide convenience to any users who related in the research field of colour feature extraction. Through experiments carried out, the colour diversity of rice seeds can be determined and classified depending on the parameters set. The colour features parameter that are extracted are red, green, blue, hue, saturation, value, and intensity. In the analysis of data, MATLAB Neural Network software was use for data research and classification. The neural network pattern recognition tool was used to create and train network, and evaluate the performance using mean square error and confusion matrices. Studies conducted for the retrain 40 hidden layer show the MSE value of 1.885E-01 and the accuracy is 76.7%. 2022-02-17T04:03:04Z 2022-02-17T04:03:04Z 2016-06 Other http://dspace.unimap.edu.my:80/xmlui/handle/123456789/74332 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 |
Machine vision Rice seed MR219 variety MR269 variety |
| spellingShingle |
Machine vision Rice seed MR219 variety MR269 variety Ahmad Yusuf, Hashim Classification of cultivated rice Seed MR219 and MR269 varieties based on colour features using machine vision technique |
| description |
Access is limited to UniMAP community. |
| author2 |
School of Bioprocess Engineering |
| author_facet |
School of Bioprocess Engineering Ahmad Yusuf, Hashim |
| format |
Other |
| author |
Ahmad Yusuf, Hashim |
| author_sort |
Ahmad Yusuf, Hashim |
| title |
Classification of cultivated rice Seed MR219 and MR269 varieties based on colour features using machine vision technique |
| title_short |
Classification of cultivated rice Seed MR219 and MR269 varieties based on colour features using machine vision technique |
| title_full |
Classification of cultivated rice Seed MR219 and MR269 varieties based on colour features using machine vision technique |
| title_fullStr |
Classification of cultivated rice Seed MR219 and MR269 varieties based on colour features using machine vision technique |
| title_full_unstemmed |
Classification of cultivated rice Seed MR219 and MR269 varieties based on colour features using machine vision technique |
| title_sort |
classification of cultivated rice seed mr219 and mr269 varieties based on colour features using machine vision technique |
| publisher |
Universiti Malaysia Perlis (UniMAP) |
| publishDate |
2022 |
| url |
http://dspace.unimap.edu.my:80/xmlui/handle/123456789/74332 |
| _version_ |
1729704626654019584 |