Handwritten Recognition based on Hand Gesture Recognition using Deterministic Finite Automata and Fuzzy Logic

Hand Gesture Recognition (HGR) is one of the most interesting branches in computer vision with lots of applications in mobiles, tablets, personal computers, and interactive platforms. The aim of this technology is to efficiently relate facilitate the people's communication with gadgets. Tracking hand movement in order to understand the desired operation can play an important role in the recognition of the hand gesture. In this paper, we propose a new approach for handwritten recognition in the context of hand gesture recognition. Our approach relies on the hand movements by means of its edge information and the movements directions. The next contribution is also minimizing the uncertainty of the handwritten recognition using fuzzy logic and deterministic finite automata (DFA). The uncertainty of the handwritten is due to the similar movements of the hands during writing the characters that we decreased it using our technique. The experimental result on real-world activities shows the success and usefulness of our approach.