Wood Chip Image Processing for AI in Agriculture Overview This project is part of a presentation at the AI in Agriculture conference, showcasing how artificial intelligence can be applied to automate wood chip image processing. The system captures images in a controlled black-box environment, ensuring consistent lighting conditions, and applies AI-driven techniques for background removal and shape extraction.
Objectives Demonstrate AI-based automation for wood chip analysis.
Improve image processing accuracy with controlled lighting conditions.
Enhance efficiency in agricultural material assessment using AI.
Features ✔ Automated Background Removal – Enhances image clarity by eliminating unwanted backgrounds. ✔ Rectangular Cutout Extraction – Detects and isolates key areas of wood chips for further analysis. ✔ Batch Processing – Efficiently processes 70 images per batch.
Conference Presentation This work highlights AI-driven automation for agricultural applications, particularly in material quality assessment. By leveraging image processing and machine learning, this approach can streamline analysis and improve precision in agricultural research.
Contributing & Future Work This research is a step towards integrating AI into agricultural automation. Contributions and suggestions are welcome for future enhancements!