A　novel　method　is　presented　based　on　image　segmentation　and　features　point　for　stereo　matching.　Firstly,　we　analyse　texture　of　the　original　image　for　distinguishing　less　texture　and　similar　texture　regions,　as　a　result,　we　can　achieve　image　segmentation　by　label　image　texture　region.　Meanwhile,　we　can　remove　smaller　regions　by　blob　filter;　Then,　SIFT　features　point　and　matching　can　achieve　reliable　and　sparse　disparity;　secondly,　we　can　gain　primly　disparity　with　SAD　area-based　matching;　Finally,　according　to　distribution　of　SIFT　matching　features,　disparity　continuous　constraint　and　minimum　distance　classifier,　we　can　be　successful　to　get　disparity　of　image　segmentation　block.　The　results　of　experiment　with　standard　test　images　show　this　paper　presents　a　method　is　effective.　Compared　with　traditional　methods,　the　method　can　obtain　quickly,　dense　and　high　precision　disparity　map.　©2009　IEEE.