The main task in Optical Character Recognition (OCR) is to get and convert all the text characters on an image as a plain text data. However, if the image has low contrast and low exposure, an issue may occur. The characters may be hidden and can't be recovered completely. One solution that has been done and reported in 2017 is by applying histogram equalization as a pre-processing step in OCR. Here, we deliver a total of 30 sample data, some of which had been used on the research's experiment reported in 2017, and some others were added later.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6727008 | PMC |
| http://dx.doi.org/10.1016/j.dib.2019.104397 | DOI Listing |
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