This study describes a new method for analyzing microcirculatory videos. It introduces algorithms for quantitative assessment of vessel length, diameter, the functional microcirculatory density distribution and red blood-cell (RBC) velocity in individual vessels as well as its distribution. The technique was validated and compared to commercial software. The method was applied to the sublingual microcirculation in a healthy volunteer and in a patient during cardiac surgery. Analysis time was reduced from hours to minutes compared to previous methods requiring manual vessel identification. Vessel diameter was detected with high accuracy (>80%, d > 3 pixels). Capillary length was estimated within 5 pixels accuracy. Velocity estimation was very accurate (>95%) in the range [2.5, 1,000] pixels/s. RBC velocity was reduced by 70% during the first 10 s of cardiac luxation. The present method has been shown to be fast and accurate and provides increased insight into the functional properties of the microcirculation.