Earticle

초록

영어

Coffee plant is a plant whose seeds called coffee beans are grown in all over the world particularly in Ethiopia. The research focuses on three major type of coffee disease which occurs on the leave part of a coffee plant, these are Coffee Leaf Rust (CLR), Coffee Berry Disease (CBD), and Coffee Wilt Disease (CWD). The aim of this paper is recognition of the three types of coffee disease using imaging and machine learning techniques. The image of Coffee plant diseases were taken from the regions of Ethiopia where more coffee is produced i.e. Southern Nations, Nationalities, and Peoples, Jimma and Zegie. In this paper artificial neural network (ANN), k-Nearest Neighbours (KNN), Naïve and a hybrid of self organizing map (SOM) and Radial basis function (RBF) are used. We conduct experiment for each group of feature set in order to get a highly correlated and the more representing features. The total number of data sets is 9100. From the total of 9100, 70% were used for training and the remaining 30% were used for testing. . In general, the overall result showed that color features represents more than texture features regarding recognition of coffee plant diseases and the performance of combination of RBF (Radial basis function) and SOM (Self organizing map) is 90.07%.

목차

Abstract
 1. Introduction
 2. Literature Review
 3. Statement of the Problem
 4. Materials and Tools
 5. Implementation Tool
 6. Design of Coffee Diseases Recognition
 7. Results
 8. Conclusion
 Acknowledgment
 References

키워드

저자

• Abrham Debasu Mengistu [ Bahir Dar University, Bahir Dar Institute of Technology, Bahir Dar, Ethiopia ]
• Dagnachew Melesew Alemayehu [ Bahir Dar University, Bahir Dar Institute of Technology, Bahir Dar, Ethiopia ]
• Seffi Gebeyehu Mengistu [ Bahir Dar University, Bahir Dar Institute of Technology, Bahir Dar, Ethiopia ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605