Traffic　safety　states　can　be　divided　into　safe　and　dangerous　according　to　the　attributes　of　video　images　of　traffic　safety　states.　We　propose　a　synergic　neural　network　recognition　model　based　on　prototype　pattern　by　analyzing　various　methods　on　intelligent　video　processing.　Our　proposed　method　realizes　real　time　classification　of　traffic　safety　states　with　high　accuracy　of　traffic　safety　states　recognition.　The　experimental　results　validate　that　the　accuracy　of　classification　of　proposed　method　arrives　at　87.5%,　increased　by　16.2%　compared　to　traditional　neural　network　methods.　©　(2013)　Trans　Tech　Publications,　Switzerland.