Version 1
: Received: 23 December 2022 / Approved: 26 December 2022 / Online: 26 December 2022 (07:30:24 CET)
How to cite:
Khan Mohd, T.; Martin Grande, A.; E. Ayala, R.; Isteefano, S. Implementing Computer Vision Techniques to Recognize American Sign Language (ASL) Hand Signals. Preprints2022, 2022120478. https://doi.org/10.20944/preprints202212.0478.v1
Khan Mohd, T.; Martin Grande, A.; E. Ayala, R.; Isteefano, S. Implementing Computer Vision Techniques to Recognize American Sign Language (ASL) Hand Signals. Preprints 2022, 2022120478. https://doi.org/10.20944/preprints202212.0478.v1
Khan Mohd, T.; Martin Grande, A.; E. Ayala, R.; Isteefano, S. Implementing Computer Vision Techniques to Recognize American Sign Language (ASL) Hand Signals. Preprints2022, 2022120478. https://doi.org/10.20944/preprints202212.0478.v1
APA Style
Khan Mohd, T., Martin Grande, A., E. Ayala, R., & Isteefano, S. (2022). Implementing Computer Vision Techniques to Recognize American Sign Language (ASL) Hand Signals. Preprints. https://doi.org/10.20944/preprints202212.0478.v1
Chicago/Turabian Style
Khan Mohd, T., Rodrigo E. Ayala and Stuart Isteefano. 2022 "Implementing Computer Vision Techniques to Recognize American Sign Language (ASL) Hand Signals" Preprints. https://doi.org/10.20944/preprints202212.0478.v1
Abstract
American Sign Language is a popular language for deaf individuals. Communication is made easier for these people through sign language. However, in a digital era like today, there is a need for these people to be able to communicate online, and even get help from technology to communicate in person with non sign language speakers. This research will present a program able to translate American sign language to plain English. This study aims to use the OpenCV library to recognize hand signals, also a trained model to identify images so that the program can then translate them to words and letters. The program uses a data set of over 2000 images which will be in this case the largest data set available. With over 90\% of accuracy it results in a basic computer program with the largest data set available that would make possible for users to communicate with a wide variety of words and expressions.
Keywords
Datasets, Neural Networks, Hand Detection, Text Tagging
Subject
Computer Science and Mathematics, Information Systems
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
