Seedling Imaging Platform for Automated Nursery Inventory Counting

The patent replaces manual mechanical counting and assessment with an automated imaging system using cameras, push bars to bend seedlings, and machine learning models to detect and count seedlings. This substitution of mechanical human labor with an automated optical-mechanical system resolves the contradiction by providing both high accuracy through algorithmic detection and high productivity through continuous automated operation.

The system enables self-service inventory assessment where the imaging system automatically captures images, the preprocessing component segments and identifies seedlings, and the machine learning model independently performs counting and quality assessment without requiring human intervention. This autonomous operation simultaneously achieves high accuracy through consistent algorithmic application and high productivity through uninterrupted automated processing.

The patent segments the complex automated inventory system into distinct functional modules: the push bar mechanism for physical seedling manipulation, the imaging system for data capture, the preprocessing component for image segmentation and feature extraction, and the machine learning model for detection and counting. This modular segmentation manages device complexity by organizing functions into separate, manageable components while maintaining high productivity through their coordinated operation.

The imaging system is designed as a universal platform that performs multiple functions: capturing images of seedlings at different growth stages, detecting seedling presence, counting individual seedlings, and assessing quality metrics. This multi-functionality reduces overall system complexity by consolidating multiple assessment tasks into a single integrated system rather than requiring separate specialized devices for each function.