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 | ||
| 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) | ||
| مراجع | ||
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