No abstract

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.

In this paper, we will discuss about the implementatoion of Histogram Equalization for images contrast enhancement, in the preprocessing step, on Optical Character Recognition(OCR). OCR has several steps, including preprocessing step. Implementing images contrast enhancement algorithm will make it easier.  It is important for images to have high level contrast. It makes those images clear. Changing the histogram will make the colors of images also change. The output will be taken to the next step processing and we will get more accurate recognition.