Aiming　to　the　problems　in　the　existing　JPEG　steganalysis　schemes,　such　as　high　redundancy　in　features　and　failure　to　make　good　use　of　the　complementarities　among　them,　this　study　proposed　a　JPEG　steganalysis　approach　based　on　feature　fusion　by　the　principal　component　analysis　(PCA)　and　analysis　of　the　complementarities　among　features.　The　study　fused　complementary　features　and　isolated　redundant　components　by　PCA,　and　finally　used　RBaggSVM　classifier　for　classification.　Experimental　results　show　that　this　scheme　effectively　improves　the　detection　rate　of　steganalysis　in　JPEG　images　and　achieves　faster　speed　of　image　classification.　©　(2013)　Trans　Tech　Publications,　Switzerland.