In this paper, a multi-scale slanted O(1) stereo (MSOS) matching algorithm is proposed. In the proposed MSOS, the concept of multi-scale propagation is introduced to handle the problem of different object size in practical applications. Moreover, the census feature, which is more robust than the original sum of absolute difference (SAD), is employed in the proposed MSOS to compensate the effect of practical situations such as radiometric change. Experimental results show that the matching performance of the proposed MSOS is greatly improved over the original SOS on the outdoor KITTI2015 dataset.