Color quality assessment of coconut sugar using artificial neural network (ANN)
This paper presents a simple color recognition algorithm using digital image processing techniques and pattern recognition to eliminate the subjectiveness of manual inspection of the quality of coconut sugar based on Philippine National Standard. The image processing was built using MATLAB functions...
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oai:animorepository.dlsu.edu.ph:faculty_research-37702022-08-25T05:59:39Z Color quality assessment of coconut sugar using artificial neural network (ANN) Aquino, Aaron U. Bautista, Mary Grace Ann C. Bandala, Argel A. Dadios, Elmer P. This paper presents a simple color recognition algorithm using digital image processing techniques and pattern recognition to eliminate the subjectiveness of manual inspection of the quality of coconut sugar based on Philippine National Standard. The image processing was built using MATLAB functions through RGB acquisition. The Backpropagation Artificial Neural Network was used in this project to enhance the accuracy and performance of image processing. The database of the network involved 300 images and 70% of these were used for training the network, 15% for validation and 15% for testing. © 2015 IEEE. 2016-01-25T08:00:00Z text https://animorepository.dlsu.edu.ph/faculty_research/2771 Faculty Research Work Animo Repository Color vision Image processing—Digital techniques Sugar Electrical and Computer Engineering Electrical and Electronics |
| institution |
De La Salle University |
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De La Salle University Library |
| continent |
Asia |
| country |
Philippines Philippines |
| content_provider |
De La Salle University Library |
| collection |
DLSU Institutional Repository |
| topic |
Color vision Image processing—Digital techniques Sugar Electrical and Computer Engineering Electrical and Electronics |
| spellingShingle |
Color vision Image processing—Digital techniques Sugar Electrical and Computer Engineering Electrical and Electronics Aquino, Aaron U. Bautista, Mary Grace Ann C. Bandala, Argel A. Dadios, Elmer P. Color quality assessment of coconut sugar using artificial neural network (ANN) |
| description |
This paper presents a simple color recognition algorithm using digital image processing techniques and pattern recognition to eliminate the subjectiveness of manual inspection of the quality of coconut sugar based on Philippine National Standard. The image processing was built using MATLAB functions through RGB acquisition. The Backpropagation Artificial Neural Network was used in this project to enhance the accuracy and performance of image processing. The database of the network involved 300 images and 70% of these were used for training the network, 15% for validation and 15% for testing. © 2015 IEEE. |
| format |
text |
| author |
Aquino, Aaron U. Bautista, Mary Grace Ann C. Bandala, Argel A. Dadios, Elmer P. |
| author_facet |
Aquino, Aaron U. Bautista, Mary Grace Ann C. Bandala, Argel A. Dadios, Elmer P. |
| author_sort |
Aquino, Aaron U. |
| title |
Color quality assessment of coconut sugar using artificial neural network (ANN) |
| title_short |
Color quality assessment of coconut sugar using artificial neural network (ANN) |
| title_full |
Color quality assessment of coconut sugar using artificial neural network (ANN) |
| title_fullStr |
Color quality assessment of coconut sugar using artificial neural network (ANN) |
| title_full_unstemmed |
Color quality assessment of coconut sugar using artificial neural network (ANN) |
| title_sort |
color quality assessment of coconut sugar using artificial neural network (ann) |
| publisher |
Animo Repository |
| publishDate |
2016 |
| url |
https://animorepository.dlsu.edu.ph/faculty_research/2771 |
| _version_ |
1743177759215058944 |