现代信息科技2025，Vol.9Issue(6)：121-125,5.DOI:10.19850/j.cnki.2096-4706.2025.06.023
基于YOLOv5的手语手势识别系统
Sign Language Gesture Recognition System Based on YOLOv5
覃博铭 1符文丝 1唐梓航1
作者信息
- 1. 桂林电子科技大学,广西 桂林 541004
- 折叠
摘要
Abstract
At present,the existing communication technologies for the deaf-mute individuals have problems such as low recognition accuracy and cumbersome equipment.This paper proposes a sign language gesture recognition system based on YOLOv5.Firstly,preprocessing such as grayscale conversion is carried out on the collected image information.The built-in functions of the OpenCV library are utilized to divide the images into local blocks and extract features,and RGB conversion is performed on the extracted samples.Secondly,the processed images are input into the model.The Adam optimizer is used to dynamically adjust the learning rate,and the K-means algorithm is adopted to calculate the appropriate anchor box values,thus improving the training speed of the model.Finally,prediction correction is carried out on the images output by the model.Redundant bounding boxes are removed through non-maximum suppression,and the final prediction results are retained.Experiments show that the training model based on YOLOv5 has a significant improvement in the accuracy and recognition rate of sign language gesture recognition.关键词
YOLOv5/手势识别/OpenCV/AdamKey words
YOLOv5/gesture recognition/OpenCV/Adam分类
信息技术与安全科学引用本文复制引用
覃博铭,符文丝,唐梓航..基于YOLOv5的手语手势识别系统[J].现代信息科技,2025,9(6):121-125,5.
