摘要
为了减轻机场跑道除胶工作人员的劳动强度,提高除胶工作效率,文章提出了一种基于机器视觉的胶痕自动查找和识别方法,设计了基于ARM单片机控制的图像无线采集和基于PC机控制的图像接收、图像预处理和图像识别系统;文章通过分析预处理后的数据特点,确定了基于细胞神经网络算法的胶痕识别算法,然后在MATLAB仿真环境下确定了该算法的最优模型和参数,最后在Visual C++6.0环境下完成了该算法的程序编译,调试并完成了对胶痕的自动识别过程;理论仿真和程序测试的结果证明了文章提出的方法在胶痕自动识别系统中的可行性,也为机场特种设备的无人化和智能化提供了参考。
In order to reduce the labor intensity of the workers cleaning the rubber marks on the runway and improve the rubber removal efficiency,this paper presents a method to recognize the rubber marks automatically based on the machine vision.The method has designed a system containing lower computer controlled by a microprocessor,wirelessly,to collect data of images of the rubber marks,and upper computer controlled by PC machine to receive,preprocess and identify them.This paper has selected a recognition algorithm based on cellular neural network by analyzing the data of the preprocessed images,and determined an optimal model and the parameters of the algorithm in the MATLAB simulation environment,then,compiled,debugged and completed the automatic recognition process of the rubber marks in the Visual C＋ ＋ 6.0.The results of simulation and test show that the cellular neural network algorithm does work in the automatic recognition system of airport runway rubber.The design and application of this system will promote the development of the unmanned and intelligent special equipments at the airport.
出处
《计算机测量与控制》
北大核心
2014年第12期4046-4049,共4页
Computer Measurement &Control
基金
国家自然科学基金项目(U1333111)
中央高校基本科研业务费资助项目(SY-1421)
关键词
跑道除胶
机器视觉
细胞神经网络
自动识别
机场特种设备
runway rubber removal
machine vision
cellular neural network
automatic recognition
special equipments
