Fig. 1. Syllable of the Tibetan. (a) Structure of the Tibetan syllable; (b) example of the Tibetan syllable; (c) examples of Tibetan transliteration of Sanskrit

Fig. 2. Original image of the historical Tibetan document

Fig. 3. Tibetan document after pre-processing

Fig. 4. Vertical segmentation process by projection of the historical Tibetan document. (a) Document line and its vertical projection; (b) character blocks in rectangular area

Fig. 5. Part of character block dataset

Fig. 6. Examples of the character segmentation challenges. (a) Segmentation challenges above the baseline; (b) segmentation challenges below the baseline

Fig. 7. Flow chart of the character segmentation for historical Tibetan document

Fig. 8. Flow chart of the local baseline detection

Fig. 9. Touching type above the baseline

Fig. 10. Schematic diagram of coordinate system and segmentation direction

Fig. 11. Examples of multipath segmentation. (a) Combination example; (b) marked skeleton diagram; (c) segmentation path

Fig. 12. Stroke types and geometric characteristics above the baseline

Fig. 13. Broken strokes type below the baseline. (a) Cross left and right; (b) cross up and down; (c) separate up and down; (d) contain

Fig. 14. Examples of strokes attribution classification. (a) With no stroke above the baseline and with no broken stroke below the baseline; (b) with strokes above the baseline and with no broken stroke below the baseline; (c) with no stroke above the baseline and with no broken stroke below the baseline; (d) with strokes above the baseline and with broken strokes below the baseline

Fig. 15. Process of local baseline detection and horizontal segmentation of character block. (a) Character blocks with syllable points; (b) character blocks with no syllable point and with no stroke above the baseline; (c) character blocks with no syllable point and with strokes above the baseline

Fig. 16. Touching stroke and type detection above the baseline

Fig. 17. Character segmentation with a touching stroke. (a) Character direction is D₁; (b) character direction is D₂

Fig. 18. Character segmentation with multiple touching strokes

Fig. 19. Character segmentation with multiple crossing strokes

Fig. 20. Statistical results of broken strokes below the baseline. (a) Cross left and right; (b) cross up and down; (c) separate up and down; (d) contain

Fig. 21. Attribution based on the horizontal distance of the centroid. (a) Character block; (b) centroid of strokes after attribution

Fig. 22. Attribution analysis of the stroke. (a) No. 1; (b) No. 9

Fig. 23. Attribution analysis of “ ” stroke

Fig. 24. Attribution analysis of both “ ” and “ ” stroks

Fig. 25. Results of character segmentation. (a) Character block; (b) block after character segmentation

Fig. 26. Wrong character segmentation caused by strokes attribution. (a)Character block; (b) local baseline and horizontal segmentation;(c) broken stroke mark; (d) result of character segmentation

Fig. 27. Wrong character segmentation caused by the baseline detection. (a) Character block; (b) horizontal projection; (c) Hough straight line detection; (d) local baseline; (e) result of character segmentation

Table 1. Classification of the character segmentation challenges

Table 2. Correct segmentation data of character block dataset

Table 3. Data of the correct segmentation in the character segmentation stage

Table 4. N_Error for each step during character segmentation

Table 5. Correctly segmented data