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Hand vein recognition with rotation feature matching based on fuzzy algorithm | ||
| International Journal of Nonlinear Analysis and Applications | ||
| دوره 12، Special Issue، اسفند 2021، صفحه 951-958 اصل مقاله (1.36 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2021.5536 | ||
| نویسندگان | ||
| Haitham S Hasan* 1؛ Mais A Al-Sharqi2 | ||
| 1Business Information Technology Department, Business Informatics College, University of Information Technology and Communications, Baghdad, Iraq. | ||
| 2Bioinformatics Department, BioMedical Informatics College, University of Information Technology and Communications, Baghdad, Iraq. | ||
| تاریخ دریافت: 16 خرداد 1400، تاریخ بازنگری: 07 مرداد 1400، تاریخ پذیرش: 30 مرداد 1400 | ||
| چکیده | ||
| The Bodily motion or emotion, which can be obtained for example from a hand or a face, originates gestures. Every individual has a unique pattern of dorsal hand veins. The vein pattern's orientation changes when one rotates their hand in a particular direction. This study focused on hand-gesture recognition using dorsal hand veins. The aim of this work is a novel technique to track and recognizing hand vein rotation using fuzzy neural network, and the change in orientation was considered as a gesture and measured. The algorithms were tested over various rotations ranging from $-45^{\circ}$ to $+45^{\circ}$. We successfully detected various rotations in both clockwise and anti-clockwise directions, achieving $93\%$ accuracy and a reasonable time execution. This problem can be solved because a person can steer a car wheel merely by rotating his/her hand. An infrared camera captured the rotation of hand veins, so car wheel steering was unnecessary. | ||
| کلیدواژهها | ||
| Complex Walsh transform؛ Dorsal hand vein pattern؛ Feature extraction؛ Fuzzy neural network؛ Sectorization | ||
| مراجع | ||
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