Widespread　application　of　biometric　authentication　brings　about　new　problem　of　privacy.　Biometric　template　protection　is　becoming　a　hot　research.　Efficient　feature　fusion　is　deemed　to　have　good　performance　possibly.　In　this　paper　we　proposed　a　fuzzy　vault　scheme　for　feature　fusion.　In　our　scheme,　two　facial　features　Multi-Block　Local　Binary　Pattern　(MB-LBP)　and　Principal　Component　Analysis　(PCA)　coefficients　are　extracted.　A　key　is　split　into　two　overlapped　subkeys.　One　is　utilized　to　generate　a　set　of　helper　data　from　MB-LBP.　The　other　is　utilized　to　generate　another　set　of　helper　data　from　PCA　coefficients.　Two　sets　of　helper　data　are　submerged　into　the　chaff　points　set　and　the　final　fuzzy　vault　is　generated.　In　the　fuzzy　vault　decoding,　the　MB-LBP　and　PCA　coefficients　of　the　query　face　image　are　utilized　to　recover　two　subkeys　from　the　fuzzy　vault.　The　final　key　is　obtained　from　two　subkeys.　Because　two　subkeys　are　overlapped　and　complementary　to　each　other,　our　scheme　can　obtain　good　authentication　performance.　It　is　confirmed　by　the　experimental　results.