This study addresses the necessity for rapid and precise measurement of micro-volume liquids （approximately 0.1 mL to 0.6 mL） within transparent tubes in industrial production settings. A machine vision-based measurement methodology is proposed， which integrates a specifically designed imaging system alongside an adaptive neighborhood-weighted brightness analysis algorithm to reliably extract the pixel length of liquid segments. This approach effectively mitigates challenges such as bubble interference， uneven lighting， and reflections from the tube's surface. Two measurement strategies are consequently introduced： the first is a calibration-based method utilizing static weighing to establish a quantitative model that correlates the pixel length of the liquid segment with the actual volume； the second is a homography-based coordinate transformation method， which translates pixel coordinates into physical space and calculates volume by incorporating the tube's inner diameter. Experimental results indicate that， under complex conditions， the proposed methods achieve measurement accuracies of approximately 98.3% and 98.4%， thereby satisfying the demands for rapid micro-volume liquid measurement in industrial applications. This methodology demonstrates significant potential for application and offers prospects for widespread adoption.