In　the　paper,　we　present　a　method　for　evaluating　the　quality　of　tongue　images　in　Traditional　Chinese　Medicine　(TCM).　First,　we　preprocess　the　original　images　to　segment　the　tongue　images.　Second,　geometric　features,　texture　features　and　spectral　entropy　features　and　spatial　entropy　features　based　on　Spatial-Spectral　Entropy-based　Quality　(SSEQ)　index　of　tongue　images　are　extracted　respectively　to　form　17　dimensional　feature　vector　for　the　tongue　image　quality　assessment.　Finally,　Support　vector　machine　(SVM)　model　is　used　to　classify　the　samples.　The　experimental　result　shows　that　our　method　has　a　better　effect　on　the　tongue　image　quality　assessment　for　the　objectification　of　tongue　diagnosis.