Automated Classification of Target Spot (Corynespora cassiicola) in Soybean Crops Using Hu Moments and Machine Learning
Abstract
This paper presents a Computer Vision approach for the automatic identification of Target Spot disease in soybeans. By utilizing Hu Invariant Moments for feature extraction and Machine Learning models, the system successfully distinguished between healthy and diseased leaves. The Decision Tree model (ExtraTrees Classifier) achieved a peak accuracy of 99.4%, proving to be an effective tool for decision support in the agribusiness sector
Fields of Study & Subjects
Smart Agriculture and AI
Industrial Vision Systems and Defect Detection
Leaf Properties and Growth Measurement
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 9 January 2026
- Language
- EN