In　this　paper,　we　present　a　text　extraction　method　for　historical　Tibetan　document　images.　The　task　of　text　extraction　is　considered　as　text　area　detection　and　location　problem.　Firstly,　the　historical　Tibetan　document　image　is　preprocessed　to　correct　imbalanced　illumination,　tilt　and　noises,　then　get　the　binary　image.　Secondly,　the　regions　of　interest　in　historical　Tibetan　documents　are　divided　into　three　categories　using　connected　components.　The　images　are　divided　equally　into　grids　and　the　grids　are　filtered　by　the　information　of　the　categories　of　CCs　and　corner　point　density.　The　remaining　grids　are　used　to　compute　vertical　and　horizontal　grid　projections.　Thirdly,　by　analyzing　the　projections,　the　approximate　location　of　the　text　area　can　be　detected.　Finally,　the　text　area　is　extracted　accurately　by　correcting　the　bounding　box　of　the　approximate　text　area.　Experiments　on　the　dataset　of　historical　Tibetan　document　images　demonstrate　the　effectiveness　of　the　proposed　method.