Ruled lines detection and removal in grey level handwritten image documents

Converting Handwritten documents to its machine written counterpart using Optical Character Recognition has many benefits like easier formatting, less storage apace, and automatic translation if needed. However, it has many noise difficulties; one of them is the ruled lines intersection with the text. In this paper, we introduce a trial to detect these ruled lines and remove them without affecting the text strokes significantly in grey-level image documents. The detection stage use Hough Transform in four squared sub-windows. And the removal stage employs intensity histogram and its entropy to isolate the text. The removal stage is followed by a morphological based enhancement for the resulting text. The proposed technique has been tested on several test real-world image documents and achieved very good results.