Abstract: Brown planthopper is one of the most important insect pest that threatens the stability of national rice production in Indonesia. One of the efforts to save rice production is by using brown planthopper resistant variety. Currently the determination approach is still conventional based on Standard Seedboxes Screening Test from IRRI with assistance of experienced experts in the scoring process resistance level.In this study, a prototype of application system to predict resistance levels by image color approach was developed. The method consists of collecting images data, preparation process (background and objects segmentation), and determination of area proportion which has been infected (sick and dead) and healthy, based on ‘A’ value from CIELab color space laboratory. According to proportion value distribution, the rule of rice resistance to brown planthopper assessment based on image was developed. The rule is mostly similar with IRRI standard rules. All of images were assessed based on the rule and then the model was developed with an error rate of 17.02%.

Elvira Nurfadhilah, Yeni Herdiyeni, Aunu Rauf and Rahmini, “Computer Vision for Screening Resistance Level of Rice Varieties to Brown Planthopper” International Journal of Advanced Computer Science and Applications(IJACSA), 6(8), 2015. http://dx.doi.org/10.14569/IJACSA.2015.060820

@article{Nurfadhilah2015,
title = {Computer Vision for Screening Resistance Level of Rice Varieties to Brown Planthopper},
journal = {International Journal of Advanced Computer Science and Applications}
doi = {10.14569/IJACSA.2015.060820},
url = {http://dx.doi.org/10.14569/IJACSA.2015.060820},
year = {2015},
publisher = {The Science and Information Organization},
volume = {6},
number = {8},
author = {Elvira Nurfadhilah and Yeni Herdiyeni and Aunu Rauf and Rahmini},
}