We　present　a　novel　and　high-precision　microscopic　vision　modeling　method,　which　can　be　used　for　3D　data　reconstruction　in　micro-gripping　system　with　stereo　light　microscope.　This　method　consists　of　four　parts:　image　distortion　correction,　disparity　distortion　correction,　initial　vision　model　and　residual　compensation　model.　First,　the　method　of　image　distortion　correction　is　proposed.　Image　data　required　by　image　distortion　correction　comes　from　stereo　images　of　calibration　sample.　The　geometric　features　of　image　distortions　can　be　predicted　though　the　shape　deformation　of　lines　constructed　by　grid　points　in　stereo　images.　Linear　and　polynomial　fitting　methods　are　applied　to　correct　image　distortions.　Second,　shape　deformation　features　of　disparity　distribution　are　discussed.　The　method　of　disparity　distortion　correction　is　proposed.　Polynomial　fitting　method　is　applied　to　correct　disparity　distortion.　Third,　a　microscopic　vision　model　is　derived,　which　consists　of　two　models,　i.e.,　initial　vision　model　and　residual　compensation　model.　We　derive　initial　vision　model　by　the　analysis　of　direct　mapping　relationship　between　object　and　image　points.　Residual　compensation　model　is　derived　based　on　the　residual　analysis　of　initial　vision　model.　The　results　show　that　with　maximum　reconstruction　distance　of　4.1　mm　in　X　direction,　2.9　mm　in　Y　direction　and　2.25　mm　in　Z　direction,　our　model　achieves　a　precision　of　0.01　mm　in　X　and　Y　directions　and　0.015　mm　in　Z　direction.　Comparison　of　our　model　with　traditional　pinhole　camera　model　shows　that　two　kinds　of　models　have　a　similar　reconstruction　precision　of　X　coordinates.　However,　traditional　pinhole　camera　model　has　a　lower　precision　of　Y　and　Z　coordinates　than　our　model.　The　method　proposed　in　this　paper　is　very　helpful　for　the　micro-gripping　system　based　on　SLM　microscopic　vision.　(C)　2016　Elsevier　Ltd.　All　rights　reserved.