A computer vision system to measure low flow rate of solid particles was developed and tested to examine its performance with various sized 7 kinds of seeds, perilla, mung bean, paddy, small red bean, black soybean, Cuba bean and small potato tuber. The test was performed for two types of particle flow, continuous and discontinuous. For the continuous flow tested with perilla, mung bean and paddy, the tests resulted correlation coefficients for the flow rates measured by the computer vision and direct method about 0.98. Average errors of the computer vision measurement were in a range of 6∼9%. For the discontinuous flow tested with small red bean, black soybean, Cuba bean and small potato tuber, the tests resulted correlation coefficients for the flow rates measured by the computer vision and direct method 0.98∼0.99. Average errors of the computer vision measurement were in a range of 5∼10%. Performance of the computer vision system was compared with that of the conventional optical sensor to count particles in discontinuous flow. The comparison was done with black soybean, Cuba bean and small potato tuber, and resulted that the computer vision has much better performance than the optical sensor in a sense of precision of the measurement.