MATLAB-Based Plant Pest Detection System with GUI Interface and SVM Classification

To better meet user requirements, we propose developing an intuitive GUI platform that enables users to capture cucumber leaf images using electronic devices, process and analyze these images, and generate diagnostic conclusions regarding cucumber leaf diseases [15]. The MATLAB implementation will process cucumber leaf images through a structured workflow: users import images from computer storage, apply processing algorithms, and save annotated results showing detected diseases. The system architecture incorporates advanced functionalities including multi-stage image processing chains (involving preprocessing, segmentation, and feature extraction) and image enhancement techniques (such as contrast adjustment and noise filtering). Additional features include program termination controls and operational flexibility through "Process Image," "Save Image," and "Exit" core functions. The platform implements state management for image reset capabilities, allowing users to revert processed images to their original state for reprocessing. A step-by-step image processing pipeline ensures systematic operation, while robust error handling manages exceptional cases. To enhance usability, we integrate screenshot functionality for image previews before processing, implemented through MATLAB's getframe and imwrite functions. These improvements collectively create a more powerful and user-friendly diagnostic platform with SVM-based classification for automated disease identification.