Segmentation of Lines and Words of Handwritten Devanagari Text using Connected Components with Statistics Method

Abstract

The pre-processing activities for handwritten Devanagari text recognition includes an significant step called Segmentation. The segmentation accuracy of Devanagari text characters depends entirely on the accurately segmented lines and words in the handwritten documents. The process of segmenting lines and words correctly leads to many issues. More detailed information is lagging on the segmentation of lines and words from Devanagari text documents, whereas it is available more for other script documents in the literature. Here, we accomplished the task of segmenting the lines and words using Connected Components with Statistics Method on PHDIndic_11 dataset. Experimentation using above mentioned method resulted in line segmentation accuracy of 91.91% and word segmentation accuracy of 72.89% which outperforms over Global threshold and Otsu’s optimum threshold methods.