A real time machine vision system for fruit size inspection was developed, which solved the problems such as fast processing the large amount of image information, improving system performance for real time dynamic image capture and processing capability, increasing precision of detection etc. For each fruit, four images were caught, and from which all the quality information of the whole surface were collected. Images were grabbed with a CCD camera (TMC-7DSP) and a frame grabber (Matrox Meteor II/MC), which is described in RGB space. The value of R/B was used as an index for image binary threshold after blurred image restoration. Median filter was used to denoise before edge detecting with Laplace Operator. A sphere fruit size-inspecting model was set up with a set of standard ball to calibrate the fruit size after the relative size of fruit, which was obtained with the method of partition edge point sets. The absolute error of the system was less than 1.1 mm and inspecting rate was over 31 fruits per second. That was this method can obtain fair inspecting speed, small absolute error, and filled the requirement of fruit automatic fruit sorting. But something is need to be paid attention, if shadow being in this vision system, it will arise big error when use partitions edge point, so it is needed to avoid the shadow.