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@article{179369,
        author = {Akshayya S and Priyadharshini Y and Sivarshana J and Supriya A},
        title = {Transforming gesture communication into speech by Speakify},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {6234-6238},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=179369},
        abstract = {This concept explores the use of OpenCV, a
popular computer vision library, for developing a realtime hand gesture recognition system. By leveraging
OpenCV’s robust image processing and analysis
capabilities, the system can detect and interpret hand
gestures from a live video stream, enabling intuitive and
natural human-computer interaction and providing us
with voice as an output. The process involves several
key steps, beginning with image acquisition, where
frames are captured and processed in real time. Next,
hand region segmentation is performed using
techniques such as skin color detection, background
subtraction, and contour detection, ensuring accurate
isolation of the hand from the background. In the
feature extraction phase, critical hand features such as
shape, contour, fingertip positions, and motion
trajectory are identified using advanced image
processing methods. Once recognized, the gestures are
mapped to corresponding voice outputs or commands,
making this technology particularly useful for sign
language interpretation and assistive communication
for individuals with speech or hearing impairments. By
implementing these steps with OpenCV functions and
machine learning algorithms, the system can recognize
a predefined set of hand gestures with high accuracy.
This gesture recognition system is not only cost-effective
but also versatile, finding potential applications in areas
like gesture-controlled user interfaces, virtual
assistants, smart home devices, and assistive
technologies for individuals with speech or hearing
impairments. In particular, it has promising
implications for sign language interpretation, enabling
more inclusive communication channels between
hearing-impaired individuals and the rest of society.},
        keywords = {OpenCV, Computer vision, Hand gesture recognition, Real-time processing, Image processing.},
        month = {May},
        }