Aiming　at　the　inherent　limitations　of　unimodal　biometric　systems,　a　multi-biometric　system　based　on　hand　vein　and　iris　was　proposed.　The　local　scale　invariant　feature　transform　(SIFT)　features　of　hand　vein　were　extracted　and　matched,　and　the　matching　ratio　of　features　between　the　registered　image　and　test　image　was　calculated　as　the　similarity　measurement.　The　feature　code　of　iris　was　extracted　from　the　detail　images　obtained　using　Haar　wavelet　transform　and　the　weighted　Hamming　distances　was　employed　to　calculate　the　similarities　between　the　patterns　in　the　database　and　the　pattern　to　be　identified.　Finally,　the　scores　from　both　matching　modules　were　sent　to　support　vector　machines　(SVM),　which　realized　the　fusion　at　the　matching　score　level　and　the　fusion　recognition　result　was　obtained.　The　performance　of　the　proposed　method　was　tested　using　the　TJU　hand　vein　image　database　and　the　CASIA　iris　database.　The　equal　error　rate　(EER)　of　the　fusion　system　is　0.02%.　Experimental　results　demonstrate　that　the　proposed　fusion　method　has　excellent　recognition　performance,　which　provides　new　scientific　approach　to　further　research　on　biometrics.