Handwritten Character Recognition in Table-Based Application

Abstract

Portable tablet PCs are very useful in relevant industry of this age because tablets are elegant in appearance and convenient to use. Important things are noted on tablet by handwriting easily in respective industry. Recognition of handwritten characters automatically on tablet like human’s brain is also necessary to be more convenient. To split each character of different handwritten styles is very difficult and it is the main challenging of handwritten character recognition. The previous handwritten character segmentation approaches are still continuing in different problems because of different handwritten styles. The combination of sliding windows, Region of Interest (ROI) box and Convolutional Neural Network (CNN) are used to execute recognition based segmentation (implicit) of handwritten characters. This system is intended to perform both segmentation and recognition of tablet based application input handwritten characters. Handwritten data are collected from 24 members of our laboratory using three tablets PC models to perform the experiments.