[1]LIANG Yihui,ZHAN Qiang.A visual platform for wireless image transmission[J].CAAI Transactions on Intelligent Systems,2016,11(5):608-612.[doi:10.11992/tis.201512014]
Copy

A visual platform for wireless image transmission

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 11 Number of periods: 2016 5 Page number: 608-612 Column: 学术论文—机器学习 Public date: 2016-11-01
Title:
A visual platform for wireless image transmission
Author(s):
LIANG Yihui;  ZHAN Qiang
School of Mechanical Engineering & Automation, Beihang University, Beijing 100191, China
Keywords:
machine vision; wireless image transmission; image processing; OpenCV; object tracking
CLC:
TP391.4
DOI:
10.11992/tis.201512014
Abstract:
In recent years machine vision has experienced increased use and application in the field of intelligent technology. However, most current visual systems have poor levels of promotability and reusability. This paper describes the basic components of a general visual system, and a hardware system designed for wireless transmission and use; this formed the basis for a vision platform using OpenCV in Linux. This platform can transmit images wirelessly via a Wi-Fi network in addition to real-time image processing. Experiments completed on the platform prove it can realize image transmitting and processing remotely according to the requirements, can provide technical support, and a development platform for the wide application of machine vision.
References:
[1] 桂卫华, 阳春华, 徐德刚, 等. 基于机器视觉的矿物浮选过程监控技术研究进展[J]. 自动化学报, 2013, 39(11):1879-1888. GUI Weihua, YANG Chunhua, XU Degang, et al. Machine-vision-based online measuring and controlling technologies for mineral flotation-a review[J]. Acta automatica sinica, 2013, 39(11):1879-1888.
[2] SZABO S, COOMBS D, HERMAN M, et al. A real-time computer vision platform for mobile robot applications[J]. Real-time imaging, 1996, 2(5):315-327.
[3] SCHINDELIN J, ARGANDA-CARRERAS I, FRISE E, et al. Fiji:an open-source platform for biological-image analysis[J]. Nature methods, 2012, 9(7):676-682.
[4] 刘焕军, 王耀南, 段峰. 机器视觉中的图像采集技术[J]. 电脑与信息技术, 2003(1):18-21. LIU Huanjun, WANG Yaonan, DUAN Feng. Image capture technology in vision image[J]. Computer and information technology, 2003(1):18-21.
[5] 张欢庆. 基于ARM处理器的嵌入式Linux系统关键技术研究[D]. 济南:山东师范大学, 2013:17-23. ZHANG Huanqing. Research of critical technologies in embedded Linux system based on ARM processor[D]. Jinan:Shandong Normal University, 2013:17-23.
[6] HU Jie, ZHANG Genbao. Research transplanting method of embedded linux kernel based on ARM platform[C]//Proceedings of the 2010 International Conference of Information Science and Management Engineering. Xi’an, China:IEEE, 2010, 2:35-38.
[7] 尤盈盈, 孟利民. 构建嵌入式linux交叉编译环境[J]. 计算机与数字工程, 2006, 34(6):30-32, 78. YOU Yingying, MENG Limin. Building embedded linux cross-compling environment[J]. Computer & digital engineering, 2006, 34(6):30-32, 78.
[8] BRADSKI G, KAEHLER A. Learning OpenCV:computer vision with the OpenCV library[M]. USA:O’Reilly Media Inc, 2008.
[9] 徐琨, 贺昱曜, 王卫亚. 基于CamShift的自适应颜色空间目标跟踪算法[J]. 计算机应用, 2009, 29(3):757-760. XU Kun, HE Yuyao, WANG Weiya. Object tracking algorithm with adaptive color space based on CamShift[J]. Journal of computer applications, 2009, 29(3):757-760.
[10] ALLEN J G, XU R Y D, JIN J S. Object tracking using camshift algorithm and multiple quantized feature spaces[C]//Proceedings of the Pan-Sydney Area Workshop on Visual Information Processing. Darlinghurst, Australia:Australian Computer Society, Inc, 2004:3-7.
[11] CHENG Yizong. Mean shift, mode seeking, and clustering[J]. IEEE transactions on pattern analysis and machine intelligence, 1995, 17(8):790-799.
Similar References:

Memo

-

Last Update: 1900-01-01

Copyright © CAAI Transactions on Intelligent Systems