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Proceedings Paper

Cloud-based application for rice moisture content measurement using image processing technique and perceptron neural network
Author(s): Febus Reidj G. Cruz; Dionis A. Padilla; Carlos C. Hortinela; Krissel C. Bucog; Mildred C. Sarto; Nirlu Sebastian A. Sia; Wen-Yaw Chung
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Paper Abstract

This study is about the determination of moisture content of milled rice using image processing technique and perceptron neural network algorithm. The algorithm involves several inputs that produces an output which is the moisture content of the milled rice. Several types of milled rice are used in this study, namely: Jasmine, Kokuyu, 5-Star, Ifugao, Malagkit, and NFA rice. The captured images are processed using MATLAB R2013a software. There is a USB dongle connected to the router which provided internet connection for online web access. The GizDuino IOT-644 is used for handling the temperature and humidity sensor, and for sending and receiving of data from computer to the cloud storage. The result is compared to the actual moisture content range using a moisture tester for milled rice. Based on results, this study provided accurate data in determining the moisture content of the milled rice.

Paper Details

Date Published: 8 February 2017
PDF: 5 pages
Proc. SPIE 10225, Eighth International Conference on Graphic and Image Processing (ICGIP 2016), 102251W (8 February 2017); doi: 10.1117/12.2266947
Show Author Affiliations
Febus Reidj G. Cruz, Mapua Institute of Technology (Philippines)
Chung Yuan Christian Univ. (Taiwan)
Dionis A. Padilla, Mapua Institute of Technology (Philippines)
Carlos C. Hortinela, Mapua Institute of Technology (Philippines)
Krissel C. Bucog, Mapua Institute of Technology (Philippines)
Mildred C. Sarto, Mapua Institute of Technology (Philippines)
Nirlu Sebastian A. Sia, Mapua Institute of Technology (Philippines)
Wen-Yaw Chung, Chung Yuan Christian Univ. (Taiwan)


Published in SPIE Proceedings Vol. 10225:
Eighth International Conference on Graphic and Image Processing (ICGIP 2016)
Yulin Wang; Tuan D. Pham; Vit Vozenilek; David Zhang; Yi Xie, Editor(s)

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