Pavement　cracks　are　the　main　manifestations　of　the　asphalt　pavement　distress　for　high-grade　highway.　Pavement　cracks　will　not　only　affect　the　road　appearance　and　the　comfort　of　driving,　but　also　easily　lead　to　structural　damage　to　pavement,　hence　shorten　the　life　of　road.　The　type　of　cracks　varies　according　to　the　cause　of　distress.　To　some　extent,　the　type　of　cracks　shows　the　extent　of　pavement　damage.　The　identification　of　the　type　of　cracks　plays　an　important　role　in　exploring　the　causes　of　distress,　detecting　the　extent　of　pavement　damage,　and　finding　a　way　to　prevent　the　distress.　In　this　paper,　based　on　support　vector　machine,　an　identification　algorithm　of　detecting　the　horizontal,　longitudinal　and　net　cracks　of　asphalt　pavement　is　proposed.　According　to　the　geometry　of　different　cracks,　we　use　the　number　of　pixels,　the　aspect　ratio,　the　level　projection,　and　the　vertical　projection　of　the　connected　area　of　the　cracks,　to　design　a　classifier　based　on　the　support　vector　machine;　and　to　identify　the　type　of　cracks.　The　experimental　results　show　that　the　rates　of　correctly　identifying　different　types　of　cracks　by　using　the　identification　algorithm　based　on　the　support　vector　machine　are　as　follows:　96.3%　for　the　horizontal　cracks,　97.2%　for　the　longitudinal　cracks,　and　94.3%　for　the　net　cracks.　Copyright　ASCE　2009.