Color quality assessment of coconut sugar using artificial neural network (ANN)

Authors

Aaron U. Aquino, De La Salle University, Manila
Mary Grace Ann C. Bautista, De La Salle University, Manila
Argel A. Bandala, De La Salle University, Manila
Elmer P. Dadios, De La Salle University, Manila

College

Gokongwei College of Engineering

Department/Unit

Electronics And Communications Engg

Document Type

Conference Proceeding

Source Title

8th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management, HNICEM 2015

Publication Date

1-25-2016

Abstract

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.

html

Digitial Object Identifier (DOI)

10.1109/HNICEM.2015.7393182

Recommended Citation

Aquino, A. U., Bautista, M. C., Bandala, A. A., & Dadios, E. P. (2016). Color quality assessment of coconut sugar using artificial neural network (ANN). 8th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management, HNICEM 2015 https://doi.org/10.1109/HNICEM.2015.7393182

Disciplines

Electrical and Computer Engineering | Electrical and Electronics

Keywords

Color vision; Image processing—Digital techniques Sugar

Upload File

wf_no