In　this　paper,　an　algorithm　through　correlation　coefficient　computation　is　proposed　for　stereo　matching　of　color　images　in　micro　stereovision.　In　this　algorithm,　the　samples　of　matching　output　are　acquired　by　the　statistics　of　multi　similarity　measurements　and　multi-matching　areas.　On　the　other　hand,　the　false　matching　results　and　the　wrong　matching　results　are　partially　filtered　by　performing　the　mean-square　error　statistics　of　matching　output　samples.　Further　more,　a　sub-pixel　matching　accuracy　is　expected　by　calculating　the　average　values　of　two　new　samples　derived　from　the　mean-square　error　statistics.　Another　problem　correlative　with　stereo　matching　algorithms,　the　performance　evaluation　of　algorithms,　is　also　discussed　by　considering　the　following　parameters,　CMSE　value,　valid　scale,　accuracy　and　single-pixel　accuracy,　etc　al.　The　experiment　results　show　that　the　stability　and　accuracy　of　stereo　matching　are　partially　improved　after　using　multi　similarity　measurements　and　multi-matching　areas,　and　an　accurate　degree　80%　is　obtained　when　mean-square　error　of　noise　is　less　than　the　value　20.　©　2011　IEEE.