Title of article
Option for optimal extraction to indicate recognition of gestures using the self-improvement of the micro genetic algorithm
Author/Authors
Talib Sabri, Bassam Department of Business Information Technology - College of Business Informatics - University of Information Technology and Communications, Baghdad, Iraq , Ahmed Yaseen AL-Falahi, Noaman Price Control and Service Quality Department - Iraqi Ministry of Communications, Baghdad, Iraq , Adil Salman, Isam Software Department - Iraqi Ministry of Communications, Baghdad, Iraq
Pages
8
From page
2295
To page
2302
Abstract
The hearing-impaired community uses gestures to communicate. Gestures can also be used in interactions between man and computer. However, gestures become increasingly complicated in a comparatively complex environment. A recognition algorithm with a choice of function based on the improved genetic algorithm is proposed to improve the ability to identify gestures. The recognition process includes retailing, extraction, and feeding functions before classifying the neural network. After learning gestures, the proposed method is compared with traditional methods that use the classic genetic algorithm. The proposed method demonstrates the effect of optimization and sensitivity of the function.
Keywords
adaptive filter , feature extraction , genetic algorithm , sign language recognition , speeded-up robust feature (SURF)
Journal title
International Journal of Nonlinear Analysis and Applications
Serial Year
2021
Record number
2702011
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