An image-processing diagnostic program for identifying common rice diseases in the Philippines

Date of Publication


Document Type

Master's Thesis

Degree Name

Master of Science in Manufacturing Engineering


Gokongwei College of Engineering


Manufacturing Engineering and Management


In the past decades various epidemics have crippled the supply of rice in the Philippines. Various methods have been created to detect crop diseases early to aid in its prevention by use of software. This study deals with the detection of four common rice diseases in the Philippines. Images of diseased rice plants are obtained from the IRRI. The .jpg files are modified by various techniques in image processing using various image software but mostly MATLAB, following this basic procedure: pre-processing, quantization, pixel classifying, and classification via decision table and matrices. The Naive-Bayes classifier is used to train and test the images according to their Lab pixel values and classify them by disease. The testing and training images are organized into datasets containing images of diseased leaves from different sources to note the effects of difference of sources in the overall analysis. iii ACKNOWLEDGEMENTS I would like to extend my deep gratitude to all the people who have helped me in the completion of this study. I would like to thank my thesis adviser, Dr. Edwin J. Calilung, for his suggestion of the thesis topic. I would like to thank the panelists, Dr. Nilo T. Bugtai, Dr. Lord Kenneth Pinpin and Prof. Arthur Pius Santiago for their help and objectivity in the proposal and final defense. Aside from the people mentioned, it is important for me to also thank the people of the International Rice Research Institute in Los Banos, Laguna, namely Dr. Casiana Vera Cruz and Ms. Isabelita Ona, for allowing me to get the images of inoculated leaves from the IRRI facility and their guidance in other matters. I would also like to thank Dr. Vladimir Mariano and Prof. Reinald Pugoy of University of the Philippines Los Banos, as well as Dr. Laurence Gan Lim of the Mechanical Engineering Department of DLSU for allowing me to consult with them regarding the algorithms I needed to use for the study.

Abstract Format






Accession Number


Shelf Location

Archives, The Learning Commons, 12F Henry Sy Sr. Hall

Physical Description

1 computer optical disc ; 4 3/4 in.

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