Automatic　tongue　image　segmentation　is　a　key　technology　for　the　research　on　tongue　characterization　in　Traditional　Chinese　Medicine.　Due　to　the　complexity　of　automatic　tongue　image　segmentation,　the　automation　degree　and　segmentation　precision　of　the　existing　methods　for　tongue　image　segmentation　are　not　satisfied.　To　address　the　above　problem,　a　method　of　automatic　tongue　image　segmentation　using　deep　neural　network　is　proposed　in　this　paper.　In　our　method,　an　image　quality　evaluation　method　based　on　brightness　statistics　is　proposed　to　judge　whether　the　input　image　is　to　be　segmented,　and　the　SegNet　is　employed　to　train　on　the　TongueDataset1　and　TongueDataset2　to　obtain　the　deep　model　for　automatic　tongue　image　segmentation.　TongueDataset1　and　TongueDataset2　are　specially　constructed　for　tongue　image　segmentation.　The　experimental　results　on　TongueDataset1　and　TongueDataset2　show　that　the　mean　intersection　over　union　score　can　reach　to　95.89%　and　90.72%,　respectively.　Compared　with　the　traditional　methods　of　tongue　image　segmentation,　our　method　can　avoid　the　complicated　process　of　extracting　features　manually,　and　has　obvious　superiority　in　the　segmentation　performance.