Character (mathematics)

Engineering

Pure mathematics

Tracking (education)

Field (mathematics)

Archaeology

Pedagogy

Joint (building)

Computer science

Numerical digit

Thresholding

Thumb

Psychology

Anatomy

Pattern recognition (psychology)

Mathematics

Image (mathematics)

Artificial intelligence

Geometry

Architectural engineering

Finger joint

Medicine

Speech recognition

Computer vision

Arithmetic

History

IEEE Transactions on Human-Machine Systems

The joint tracking-based writing system refers to writing characters by changing the position of the finger joint. It is a new research field in interaction-based input systems. However, joint tracking is a very challenging task. In this article, we present a new method for a finger-joint tracking-based character recognition system using a 3-D camera. The proposed method tracks the finger-joint from 3-D information to identify a numerical digit, alphabet, character, special key, or symbol using the distance between the thumb tip and another finger-joint. The recognition is based on Euclidean distance thresholding and geometric slope techniques. Joint data are stored in a 3-D matrix to assign the 3-D coordinate values. The exact character is identified according to the specified definitions. First, a single hand-based digit recognition method is introduced, in which the left or right hand is used. Second, a double hand-based writing system is presented in which both hands are used simultaneously; this system features a full keyboard with 124 different characters. Our results show an overall accuracy of 91.95% and 91.85% for single-hand and double-hand recognition, respectively; with a recognition time of less than 60 ms for each character. An important contribution of this article is that the proposed system can work in both light and dark environments, requires only a small computation area and has a large number of character sets (124 characters). In addition, a region-based user study has been conducted to verify the approach.

Implementation of a Character Recognition System Based on Finger-Joint Tracking Using a Depth Camera