Application of visual recognition technology in intelligent blood collection tube sorting system

This paper investigates the application of visual recognition technology in the blood collection tube sorting system. The system achieves automatic recognition and classification of blood sample color, liquid level height, and morphology through image acquisition, processing, and analysis combined with deep learning algorithms. Experimental results demonstrate that the application of visual recognition technology in the sorting system can remarkably enhance the system's intelligence level, recognition accuracy, and processing speed.