Tomato　localization　is　the　main　difficulty　of　tomato　picking　robots　vision　system.　To　provide　robots　vision　system　with　the　accurate　position　of　tomatoes,　this　paper　collects　images　with　a　binocular　camera,　provides　the　principle　of　binocular　ranging,　and　improves　the　census　stereo　matching　algorithm.　The　improved　algorithm　betters　the　area　matching　process:　only　the　areas　con-taining　tomatoes　are　matched,　more　constraints　are　applied　on　the　area　matching,　and　the　Local-ization　of　tomatoes　in　overlapping　areas　is　optimized.　Compared　with　stereo　processing　by　semiglobal　matching　and　mutual　information　(SGBM)　algorithm　and　pyramid　stereo　matching　net-work　(PSMnet),　the　improved　algorithm　achieved　an　extremely　small　disparity　error.　The　absolute　error　maximized　at　4　pixels.　The　matching　time　for　a　single　image　was　10　ms　at　the　most.　In　this　way,　the　matching　time　is　improved　significantly.　Experimental　results　show　that　the　improved　cen-sus　matching　algorithm　provided　tomato　picking　robots　vision　system　with　more　accurate　localiza-tion　information,　and　greatly　improved　the　picking　efficiency.(c)　2022　THE　AUTHORS.　Published　by　Elsevier　BV　on　behalf　of　Faculty　of　Engineering,　Alexandria　University.　This　is　an　open　access　article　under　the　CC　BY-NC-ND　license　(http://creativecommons.org/　licenses/by-nc-nd/4.0/).