Non-destructive　detection　of　wire　bonding　defects　in　integrated　circuits　(IC)　is　critical　for　ensuring　product　quality　after　packaging.　Image-processing-based　methods　do　not　provide　a　detailed　evaluation　of　the　three-dimensional　defects　of　the　bonding　wire.　Therefore,　a　method　of　3D　reconstruction　and　pattern　recognition　of　wire　defects　based　on　stereo　vision,　which　can　achieve　non-destructive　detection　of　bonding　wire　defects　is　proposed.　The　contour　features　of　bonding　wires　and　other　electronic　components　in　the　depth　image　is　analysed　to　complete　the　3D　reconstruction　of　the　bonding　wires.　Especially　to　filter　the　noisy　point　cloud　and　obtain　an　accurate　point　cloud　of　the　bonding　wire　surface,　a　point　cloud　segmentation　method　based　on　spatial　surface　feature　detection　(SFD)　was　proposed.　SFD　can　extract　more　distinct　features　from　the　bonding　wire　surface　during　the　point　cloud　segmentation　process.　Furthermore,　in　the　defect　detection　process,　a　directional　discretisation　descriptor　with　multiple　local　normal　vectors　is　designed　for　defect　pattern　recognition　of　bonding　wires.　The　descriptor　combines　local　and　global　features　of　wire　and　can　describe　the　spatial　variation　trends　and　structural　features　of　wires.　The　experimental　results　show　that　the　method　can　complete　the　3D　reconstruction　and　defect　pattern　recognition　of　bonding　wires,　and　the　average　accuracy　of　defect　recognition　is　96.47%,　which　meets　the　production　requirements　of　bonding　wire　defect　detection.