• R. Siji
• Dr. S. Nithya

For the hearing-impaired and deaf society sign language (SL) is a crucial interaction tool. SL, is viewed as a highly organized and ordered form among the different gesture types in the interactive hand gesture taxonomies. People with hearing impairments communicate through signs in visual space rather than through speech or sounds [1]. SL examines non-manual signs, such as facial expressions and other body poses, that transmit semantic information in addition to hand movements. Understanding of SL is one particular area of interest [2,3]. Current methods utilized in research on hand gesture and SL recognition are examined in this study. Hand gestures are utilized as signs, and films and pictures can be used to recognize these motions. Based on the characteristics of the gesture image, hand movements are recognized and categorized. Different approaches for extracting features are used to find them, and machine learning (ML) and deep learning (DL)methods are employed for categorizing them [4]. Reviewing the primary findings of a comparison of feature extraction techniques of comparable systems employed in image-based hand gesture identification according to accuracy rate is the paper's primary contribution. In summary, the work aims to offer readers a thorough overview of automated gesture and SL identification, while also advancing study endeavors in this domain.

Classification, feature extraction, hand gesture recognition, sign language recognition, recognition accuracy.

"A REVIEW OF VARIOUS APPROCHES FOR HUMAN HAND GESTURE RECOGNITION AND CLASSIFICATION OF SIGN LANGUAGE DATA", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 1, page no.d413-d418, January-2024, Available :http://www.jetir.org/papers/JETIR2401351.pdf

"A REVIEW OF VARIOUS APPROCHES FOR HUMAN HAND GESTURE RECOGNITION AND CLASSIFICATION OF SIGN LANGUAGE DATA", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 1, page no. ppd413-d418, January-2024, Available at : http://www.jetir.org/papers/JETIR2401351.pdf