In the realm of agricultural quality control, accurately categorizing cocoa beans based on their physical characteristics is essential for ensuring product quality and optimizing processing workflows. To address this need, a sophisticated image processing system was developed utilizing National Instruments’ LabVIEW platform in conjunction with Vision Assistant, a powerful tool for creating and deploying vision algorithms.
This system was specifically designed to analyze cocoa beans, leveraging various parameters and metrics such as size, height, width, and other morphological features to categorize beans into different classes. The goal was to automate the inspection process, reduce manual errors, and improve throughput.
System Overview
The cocoa bean classification system integrates image acquisition hardware with LabVIEW-based processing routines. The core components include:
- Image Capture Module:Â High-resolution cameras capture images of cocoa beans on a conveyor or in a controlled environment.
- Preprocessing:Â Images are preprocessed to improve clarity, contrast, and to reduce noise, ensuring reliable feature extraction.
- Feature Extraction:Â Using Vision Assistant, relevant parameters such as size, height, width, and other morphological metrics are calculated.
- Classification Logic:Â Extracted features are analyzed against predefined thresholds or models to categorize each bean into classes such as “good,” “defective,” “small,” or “large.”
- Output and Sorting:Â Based on classification, the system can trigger sorting mechanisms or generate reports.