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Sabri, Bassam, Yaseen AL-Falahi, Noaman, Salman, Isam. (1400). Option for optimal extraction to indicate recognition of gestures using the self-improvement of the micro genetic algorithm. نشریه هنرهای کاربردی, 12(2), 2295-2302. doi: 10.22075/ijnaa.2021.5375
Bassam Talib Sabri; Noaman Ahmed Yaseen AL-Falahi; Isam Adil Salman. "Option for optimal extraction to indicate recognition of gestures using the self-improvement of the micro genetic algorithm". نشریه هنرهای کاربردی, 12, 2, 1400, 2295-2302. doi: 10.22075/ijnaa.2021.5375
Sabri, Bassam, Yaseen AL-Falahi, Noaman, Salman, Isam. (1400). 'Option for optimal extraction to indicate recognition of gestures using the self-improvement of the micro genetic algorithm', نشریه هنرهای کاربردی, 12(2), pp. 2295-2302. doi: 10.22075/ijnaa.2021.5375
Sabri, Bassam, Yaseen AL-Falahi, Noaman, Salman, Isam. Option for optimal extraction to indicate recognition of gestures using the self-improvement of the micro genetic algorithm. نشریه هنرهای کاربردی, 1400; 12(2): 2295-2302. doi: 10.22075/ijnaa.2021.5375

Option for optimal extraction to indicate recognition of gestures using the self-improvement of the micro genetic algorithm

International Journal of Nonlinear Analysis and Applications
دوره 12، شماره 2، بهمن 2021، صفحه 2295-2302    اصل مقاله (366.84 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22075/ijnaa.2021.5375
نویسندگان
Bassam Talib Sabri* 1؛ Noaman Ahmed Yaseen AL-Falahi2؛ Isam Adil Salman3
1Department of Business Information Technology, College of Business Informatics, University of Information Technology and Communications, Baghdad, Iraq
2Director of Price Control and Service Quality Department, Chief programmer, Iraqi Ministry of Communications, Baghdad, Iraq
3Associate Director of the Software Department, Senior chief of Programs, Iraqi Ministry of Communications, Baghdad, Iraq
تاریخ دریافت: 27 اسفند 1399،  تاریخ بازنگری: 02 تیر 1400،  تاریخ پذیرش: 20 تیر 1400 
چکیده
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.
کلیدواژه‌ها
adaptive filter؛ feature extraction؛ genetic algorithm؛ sign language recognition؛ speeded-up robust feature (SURF)
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