A　novel　approach　of　blind　steganalysis　is　proposed,　which　is　based　on　image　texture　energy-entropy　features.　Image　complexity　describes　the　difference　of　image＇s　content　and　texture.　Steg-image＇s　texture　is　ordinarily　more　complicated　than　that　of　cover　image.　For　analyzing　image　complexity,　using　image　texture　features　to　measure　the　statistical　differences　between　cover　image　and　steg-image.　In　the　paper,　we　analyze　image　complexity　based　on　image　texture　segmentation　technique,　and　use　Laws＇　image　texture　energy-entropy　features　to　measure　the　statistical　differences　between　cover　image　and　steg-image.　Applying　these　texture　features,　blind　steganalysis　is　implemented.　Support　Vector　Machine　(SVM)　is　used　as　classifier　to　distinguish　whether　a　given　image　is　embedded　into　the　convert　message.　Experiment　results　show　that　the　proposed　approach　is　greatly　valuable　and　our　blind　steganalysis　method　attains　a　good　testing　accurate　rate.