An Approach for Morse Code Translation from Eye Blinks Using Tree Based Machine Learning Algorithms and OpenCV

• Published in: Journal of physics. Conference series Vol. 1921; no. 1; pp. 12070 - 12079
• Main Authors: Sumanth Naga Deepak, G, Rohit, B, Akhil, Ch, Sai Surya Chandra Bharath, D, Prakash, Kolla Bhanu
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.05.2021
• Subjects: Algorithms; Blinking; Communication; Eye blink; Hand gestures; Machine learning; Morse code; OpenCV; Physics; Sign language; Webcams
• ISSN: 1742-6588; 1742-6596
• DOI: 10.1088/1742-6596/1921/1/012070

For ages, human beings have been communicating with one another through different modes of communication. Communication is a process through which a person can communicate his/her feelings and thoughts to the other person. To communicate we can do it through either speech or sign language. The spoken language is used by abled persons, While the differently abled persons (deaf and dumb) may find it difficult to understand the same. So, for effective communication between the differently abled and abled person sign language has been developed. For private communication between two people, morse code has been developed which is highly efficient to exchange secrets. It also helps in emergencies where a person cannot communicate through hand gestures. Different methods/modes are used in morse code, but our focus is on eye blinking. Our approach towards this area has been to implement morse code using eye blinks in real-time assistance using a webcam to provide predicting power based on machine learning’s tree algorithms.