In recent years, air writing has become one of the most challenging and exciting research areas in image processing and pattern recognition.
The project employs object tracking techniques to construct a motion-to-text converter that might be used as software in the field of education to allow students and teachers to write in the air. The project generates letters on the screen by utilizing computer vision to trace the path of a finger or an object. The resulting text can be utilized for a variety of things, including solving graph-related challenges. Questions on logical reasoning (Mathematics), to write formulas or execute derivations, Kindergarten kids are being taught the alphabet, to replace chalk and board (dustless classroom) in offline classes, etc. For the deaf, it will be a strong way of communication.
The aim of our project is to make an inexpensive product that lets the user write in air using any object with ease and to improve the online learning experience by solving problems that need the use of expensive products such as stylus or touch screen.
The objective following this aim is to make Virtual Canvas user friendly by incorporating features to save, undo, maximize/minimize brush size and whiteboard for cluttered backgrounds. Another objective is to create an environmentally friendly product which decreases the use of chalk or colored markers which are considered harmful for the environment as well as human health.
The model is created using the Python programming language.
The gestures will be controlled using OpenCV (Open Source Computer Vision) which makes use of a video camera (laptop or computer) to track the user gestures.
NumPy is used for signal processing and also for some numerical operations.
Tkinter is used to create the user interface at the start of the software and to select the object color.
The keyboard will be used to track the user inputs or shortcuts to save, undo, change color and clear the screen.