Morse code is one of the oldest communication techniques used in telecommunication systems. It can be transmitted as a visual signal by using reflections or flashlights, but it can also be used as a non-detectable form of communication by tapping fingers or even blinking eyes. 

Researchers from the Vellore Institute of Technology has formulated a computer vision-based approach that automatically characterises the characters conveyed, wherein a person can communicate to the system or another person through Morse code with eye gestures. Users can decode this visual eye-tracking-based language with the help of our automatic computer vision-driven method. Their approach uses a standard webcam to detect the eye gestures, which are interpreted as dots and dashes. These dots and dashes are used to represent the Morse code-based words.

Developing the model

The researchers employed image processing techniques-based blink and pupil detectors. A blink detector helps us detect a blink and the time it takes for each blink. A blink that takes 2 to 4 seconds is acknowledged as a dot, whereas a blink that takes more than 4 seconds is represented as a dash. 

The pupil detector helps us to detect the movement of the pupils, and if pupils move towards the right with respect to a person, then it is acknowledged as the following letter, and if the pupils are moved towards the left with respect to a person, then it is acknowledged as the next word. In this way, they could decode the Morse code, which will be communicated using eyes and establish a non-detectable communication between a person and an automatic system.

This study on an unconstrained visual scene with preliminary greeting words indicates the promise of an automatic eye-tracking-based system with a success rate of 98.25% that can be used in nonverbal communications.

AI and Morse Code translation

This is not the first time that AI researchers have attempted to leverage AI-based technology for translating Morse Code. In a paper titled “Creating an AI-Enhanced Morse Code Translation System Based on Images for People with Severe Disabilities,” a group of Taiwanese researchers designed a set of image-assistive communication equipment based on artificial intelligence to solve communication problems of daily needs.

The researchers used artificial intelligence for facial positioning and facial-motion-recognition-generated Morse code and then translated it into readable characters or commands. This system allows users to express their thoughts and needs through their facial movements, thereby improving their quality of life and having an independent living space. Moreover, the system can be used without touching external switches, significantly improving convenience and safety.

Numerous AI techniques can be used in Morse Code translation. Some are Automated Morse Coding, Visual Morse Code Recognition, Morse Code Translation Apps, and Morse Code-to-Text Speech Recognition. 

Two-century-old technologies like Morse code have not become obsolete in the digital era. The introduction of AI has reviewed the use of Morse code across different eras and revived it across different areas. Innovation still finds an unending place in humanity, and in this very sense, the resurrection of Morse code stands testimony to such.

Journal of Mobile Multimedia

MDPI

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