TY - JOUR
AU1 - Kumar, Rakesh
AB - It is an open era of research to provide the assistance communication to hearing and visually impaired people. For the same, this paper proposed a recognition and classification of hand gesture to identify the correct denotation with maximum accurateness for standard American Sign Language. The proposal intelligently used the information based on image contours to identify the character’s representation of hand gesture. The proposal optimizes the performance overhead through identifications of 17 characters and 6 symbols based on image contours and convexity measurement of Standard American Sign Language without using complex algorithms and specialized hardware devices. Accuracy measurement done through simulation, which shows how our proposal provide more accuracy with minimum complexity in comparison to other state-of-art works.
TI - An Improved Hand Gesture Recognition Algorithm based on image contours to Identify the American Sign Language
JF - IOP Conference Series: Materials Science and Engineering
DO - 10.1088/1757-899X/1116/1/012115
DA - 2021-05-27
UR - https://www.deepdyve.com/lp/iop-publishing/an-improved-hand-gesture-recognition-algorithm-based-on-image-contours-171ZskuP7s
SP - 012115
VL - 1116
IS - 1
DP - DeepDyve
ER -