The Vision Detection System Based on Gesture Recognition

Computer & Telecommunication

2019, Vol. 1

Issue (3): 5-8 DOI:

Current Issue | Archive | Adv Search

The Vision Detection System Based on Gesture Recognition

ZHANG Qin

Wuhan Technical College of Communications

Download:

PDF(0KB)
Export: BibTeX | EndNote (RIS)

Abstract This design realizes a vision detection system, which can detect human visual acuity through gesture recognition technology. The system includes several modules: acquisition, data storage and conversion, gesture recognition and output control. And the camera, memory, display and speaker are connected externally. The visual icon "E" is displayed on the display screen, and then people use gestures to indicate the direction of "E". After the camera captures the image, the system recognizes and judges the direction of gesture, and then compares the correct direction to detect the visual acuity of people. Because the system eliminates manual detection, it is convenient, accurate and it saves manpower. The system realizes dynamic gesture interaction, being interesting and easy to be popularized.

Key words： vision detection image acquisition gesture recognition image processing

Published: 05 August 2019

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	ZHANG Qin

Cite this article:

ZHANG Qin. The Vision Detection System Based on Gesture Recognition. Computer & Telecommunication, 2019, 1(3): 5-8.

URL:

http://www.computertelecom.com.cn/EN/ OR http://www.computertelecom.com.cn/EN/Y2019/V1/I3/5

[1]	WENG Geng-peng ZHENG Xiao-fan PAN Liang RAO Hao. Analysis of Gesture Recognition Model Based on Mobile Device[J]. 电脑与电信, 2021, 1(8): 22-25.
[2]	YAO Bing-ying YANG Wei CHEN Jian-qiang. Research and Practice of Teaching Software in Digital Image Processing Experiment[J]. 电脑与电信, 2020, 1(9): 29-33.
[3]	LIU Li-pei MAYu-xing LU Ya-ting WANG Qiang YANG Zhuang. The Fifth RMB Face Value Recognition System Design Based on MATLAB[J]. 电脑与电信, 2020, 1(7): 28-31.
[4]	ZHENG Lian-hong CHEN Zhao-yan WANG Xiao-yin WANG Si-fan. Recognition of Vortex Based on OpenCV[J]. 电脑与电信, 2020, 1(4): 30-35.
[5]	XIE Shumin DENG Lei XIE Zhong-mei LI Hai-ping. DenoisingAlgorithm Based on Convolutional Neural Network in Real Scene[J]. 电脑与电信, 2020, 1(11): 39-43.
[6]	DING Ze-yu GONG Wei. Research on Dynamic Gesture Recognition Based on Hidden Markov Model[J]. 电脑与电信, 2019, 1(5): 33-36.
[7]	YI Li-zhi. Research and Application of Image Clarity Processing in Haze Environment[J]. 电脑与电信, 2019, 1(4): 1-4.
[8]	LI Huan-chen. Pavement Crack Detection Based on Enhanced Convolution Neural Network[J]. 电脑与电信, 2018, 1(11): 54-56.
[9]	YuWei, Li Yuxiang. Design and Implementation of Online Image Processing System Based on ASP.NET[J]. 电脑与电信, 2016, 1(4): 72-74.
[10]	Guo Zhonghua, Lian Yidong, Wu Fengjie, Xiang Guangcheng, Yang Zhi. Design of Embedded Face Image Acquisition and Display System[J]. 电脑与电信, 2015, 1(7): 32-34.
[11]	Xiao Jianliang Qu Yumeng. Simple License Plate Recognition Algorithm and Implementation [J]. , 2011, 1(10): 0-0.
[12]	Zhang Jun. Image Processing with Wavelet Transformation in MATLAB[J]. , 2011, 1(09): 0-0.
[13]	Chen Yanlong . Improved Edge Detection Algorithm Based on Canny Operator and Particle Swarm Optimization[J]. , 2011, 1(05): 0-0.
[14]	Liu　Cuiyan. Image Processing Mathod and Anysis Based on MATLAB[J]. , 2009, 1(4): 84-86.

Viewed

Full text

Abstract

Cited

Shared

Discussed