Deteksi Gestur Tangan Berbasis Pengolahan Citra

Abdullah Sani, Suci Rahmadinni
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引用次数: 1

Abstract

—Hand sign language is a medium of communication for people with disabilities (deaf and speech impaired). However, in social practice, persons with disabilities may have to communicate with non-disable persons who do not understand sign language. These problems can be overcome with the help of translators or normal people learning sign language through existing media such as videos. Unfortunately, this method will probably cost a lot of money and time. In respons to this issue, the present study designed a sistem to detect hand gestures based on image processing. The method used is the You Only Look Once (YOLO) algorithm. The YOLO algorithm can detect and classify objects at once without being influenced by the light intensity and background of the object. This algorithm is a deep learning method that is more accurate than other deep learning methods. From this research, the system can detect and classify hand gestures with different backgrounds, light intensity, and distances with an accuracy rate above 90%.
手持式图像处理检测
-手语是残疾人(聋人和语言障碍者)的交流媒介。然而,在社会实践中,残疾人可能不得不与不懂手语的非残疾人进行交流。这些问题可以在翻译人员的帮助下或通过视频等现有媒体学习手语的普通人的帮助下克服。不幸的是,这种方法可能会花费大量的金钱和时间。针对这一问题,本研究设计了一个基于图像处理的手势检测系统。使用的方法是You Only Look Once (YOLO)算法。YOLO算法可以在不受物体光强和背景影响的情况下对物体进行一次性检测和分类。该算法是一种深度学习方法,比其他深度学习方法更准确。通过本研究,该系统可以对不同背景、光照强度和距离的手势进行检测和分类,准确率在90%以上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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24
审稿时长
24 weeks
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