Computer Vision for Screening Resistance Level of Rice Varieties to Brown Planthopper

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%.

Authors and Affiliations

Elvira Nurfadhilah, Yeni Herdiyeni, Aunu Rauf, Rahmini

Keywords

Related Articles

Model and Criteria for the Automated Refactoring of the UML Class Diagrams

Many papers have been written on the challenges of the software refactoring. The question is which refactorings can be applied on the modelling level. Based on the UML model, for example. With the aim of evaluating this...

LSSCW: A Lightweight Security Scheme for Cluster based Wireless Sensor Network

In last two decades, Wireless Sensor Network (WSN) is used for large number of Internet of Things (IoT) applications, such as military surveillance, forest fire detection, healthcare, precision agriculture and smart home...

PSO Algorithm based Adaptive Median Filter for Noise Removal in Image Processing Application

A adaptive Switching median filter for salt and pepper noise removal based on genetic algorithm is presented. Proposed filter consist of two stages, a noise detector stage and a noise filtering stage. Particle swarm opti...

A Digital Ecosystem-based Framework for Math Search Systems 

 Text-based search engines fall short in retrieving structured information. When searching for x(y+z) using those search engines, for example Google, it retrieves documents that contain xyz, x+y=z, (x+y+z) =xyz or a...

Comparative Analysis of Support Vector Machine, Maximum Likelihood and Neural Network Classification on Multispectral Remote Sensing Data

Land cover classification is an essential process in many remote sensing applications. Classification based on supervised methods have been preferred by many due to its practicality, accuracy and objectivity compared to...

Download PDF file
  • EP ID EP143176
  • DOI 10.14569/IJACSA.2015.060820
  • Views 80
  • Downloads 0

How To Cite

Elvira Nurfadhilah, Yeni Herdiyeni, Aunu Rauf, Rahmini (2015). Computer Vision for Screening Resistance Level of Rice Varieties to Brown Planthopper. International Journal of Advanced Computer Science & Applications, 6(8), 149-154. https://europub.co.uk/articles/-A-143176