An automated test tube identification and sorting system based on machine vision

Yanhao Jing

doi:10.1117/12.3036665

13 July 2024 An automated test tube identification and sorting system based on machine vision

Yanhao Jing

Proceedings Volume 13208, Third International Conference on Biomedical and Intelligent Systems (IC-BIS 2024); 132081K (2024) https://doi.org/10.1117/12.3036665
Event: 3rd International Conference on Biomedical and Intelligent Systems (IC-BIS 2024), 2024, Nanchang, China

Abstract

This research presents a machine vision system for automated test tube identification and sorting in medical laboratories, improving upon manual methods that are error-prone and inefficient. The system employs digital image processing to detect specimen presence via tube caps, enhancing accuracy and throughput. The setup includes a transparent test tube rack with CCD cameras capturing images against a black background. Images are processed from RGB to HSI format for better color differentiation and smoothed to reduce noise. Edge and circle detection algorithms pinpoint the locations of test tubes for robotic arm sorting. Experiments across various filling scenarios validate the system's effectiveness. The system promises to reduce human error, optimize lab workflows, and increase automation in healthcare diagnostics.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yanhao Jing "An automated test tube identification and sorting system based on machine vision", Proc. SPIE 13208, Third International Conference on Biomedical and Intelligent Systems (IC-BIS 2024), 132081K (13 July 2024); https://doi.org/10.1117/12.3036665

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