A Universal Way to Collect and Process Handwritten Data for Any Language

Abstract

In recent years researches based on Machine learning and Deep learning have achieved much interest and one of its handwritten recognition. Handwritten recognition is very difficult due to its lack of dataset and also for collecting data from people. This research introduces a fast and comprehensive way to collect and process handwritten data to develop a way of Handwritten Recognition (HWR) algorithm for any languages. In this research handwritten characters wrote on a paper and then scanned to get the data into a JPEG format. We also focused on some of the other issues and requirements while collecting handwritten data, creating form, data collection methodology, process, using software and relevant tools. We described these issues in the context of our own effort to create a handwritten database for the Bangla language. Our designed Graphical User Interface (GUI) is also able to process 100 scanned images per minute where each scanned image contains 120 characters.