As　a　shining　pearl　in　traditional　Tibetan　culture,　historical　Tibetan　documents　have　received　extensive　attention　from　historians,　linguists　and　Buddhist　scholars.　These　documents　are　converted　into　digital　form　using　Tibetan　document　segmentation　and　recognition　methods.　The　document　digitization　is　of　great　significance　for　the　research,　protection　and　inheritance　of　Tibetan　history.　This　paper　proposes　an　overall　segmentation　and　recognition　framework　for　historical　Tibetan　document　images.　Firstly,　the　historical　Tibetan　document　image　is　preprocessed　to　correct　imbalanced　illumination,　tilt　and　noises,　and　is　further　transformed　into　the　binarized　image.　Secondly,　we　propose　a　layout　segmentation　method　based　on　block　projection　to　segment　Tibetan　document　images　into　texts,　lines　and　frames.　Thirdly,　in　order　to　solve　the　problems　of　touching　strokes　between　text-lines　and　curvilinear　text-lines,　we　present　a　text-line　segmentation　method　based　on　graph　model　for　historical　Tibetan　text-line　segmentation.　Lastly,　we　present　a　touching　segmentation　method　to　segment　touching　Tibetan　character　string,　and　then　recognize　Tibetan　characters.　Experimental　results　show　our　proposed　methods　on　layout　segmentation,　text-line　segmentation　and　touching　character　string　segmentation,　achieve　the　satisfactory　performance.　The　proposed　methods　can　also　be　applied　to　other　fonts　in　Tibetan　font　family.