Digitization of Handwritten Documents Using Image Processing

With the rising use of digital technology to store and transmit information in many industries and practically all day-to-day activities, handwriting character recognition has become a major study topic. It finds importance in fields such as medical, banking, and historic sectors. Considering the vast amount of handwritten data, it becomes useful and important to digitize this text so. A major part of this process is to improve the quality of the document images, followed by recognition of the text. Handwriting text recognition refers to a computer’s capacity to recognize and interpret understandable handwriting input from a variety of sources, including touch screens, pictures, paper documents, and other sources. Because everyone has a different handwriting style, handwritten text, and its constituent characters remain complicated. This research aims to explore various image processing techniques to digitize handwritten data and study their performances. These performances have been validated using a simple recognition model that determines the effectiveness of the preprocessing done on the images.