Author(s)

Mahmoud Zaki Iskandarani

Faculty of Science and Information Technology, Al-Zaytoonah University of Jordan, Amman, Jordan.

Many formal institutions, companies, hospitals, laboratories need some time to exchange hand signed reports through modern communication means such as Fax, E-mails, and others. A problem is faced due to the quality of both scanned documents and originally used paper, which results in problems in converting such images to text. In addition, font type and size, contrast and background darkness have an adverse effect on the accuracy of the resulted text. Thus, an investigation into the relationship between scanned document zoom and scanning resolution in Dots per Inch (DPI) for a special case and type of scanned forms is carried out to enable design of an algorithm that takes into account such cases. It is found that a much higher level of zooming and resolution is needed to achieve acceptable recognition for the special case of dark, low contrast, small font forms. It is also found that the optimum zooming level is set by the number of recognized words as they are more difficult to learn and analyze.

OCR, Zoom, Scanning, Forms Recognition, Data Mining

Iskandarani, M. (2015) Improving the OCR of Low Contrast, Small Fonts, Dark Background Forms Using Correlated Zoom and Resolution Technique (CZRT). Journal of Data Analysis and Information Processing, 3, 34-42. doi: 10.4236/jdaip.2015.33005.