期刊文献+

基于PCNN的桨叶图像提取及锥度测量 被引量:1

A New Method for Rotor Blade Image Extraction Based on PCNN and Pyramid Angle measurement
下载PDF
导出
摘要 针对目前对直升机桨叶共锥度测量难度大、精度低、无法对桨叶逐点测量的缺点,提出了一种应用视觉系统测量旋翼共锥度的新方法,给出了系统的总体安装方案并对系统的成像误差精度进行了分析,由于旋翼桨叶处于高速旋转状态需要实时处理的特点,提出了一种基于脉冲耦合神经网络(PCNN)的分割方法,在设计好的旋翼桨叶模型上进行了相关实验,通过与其它分割算法的对比,验证了算法的具有很高的识别率;实验结果表明:基于PCNN的分割方法具有较高的精度,适用于实时的旋翼锥度测量系统。 According to the problems for helicopter blades pyramid angle measurement, such as great difficulty of the measuring, low accuracy and thoroughly examination hardly, this paper presents a new method applied to helicopter blade pyramid angle measurement by using vision system, the overall design scheme of the system is offered and the imaging error is analyzed. Because the rotor blades rotated at a high speed and need real--time processing, proposes a image segmentation method based on Pulse Couple Neural Network (PCNN), the related experiment to the rotor blades model validates the PCNN algorithm has the advantage in recognition rate compared with other segmentation algorithms. The experimental results show the method has higher accuracy and suitable for blades pyramid measurement system.
出处 《计算机测量与控制》 CSCD 北大核心 2011年第3期559-561,567,共4页 Computer Measurement &Control
基金 国家自然科学基金全景图像分辨率增强方法研究(60875025)
关键词 桨叶共锥度 精度分析 脉冲耦合神经网络(PCNN) 旋翼桨叶模型 blades pyramid angle accuracy analysis PCNN rotor blades model
  • 相关文献

参考文献8

二级参考文献46

共引文献215

同被引文献8

  • 1(英)尼克松(Nixon,M.S.),(英)阿瓜多(Aguado,A.S.).特征提取与图像处理,第2版[M].李实英,杨高波,译一E京:电子工业出版社.2010.
  • 2M.C. Morrone, J.R. Ross, D.C. Burr, and R.A. Owens. Mach bands are phase dependent[J]. Nature. 1986, 324(6094): 250-253.
  • 3MORRONE M C,OWENS R A.Feature detection from local energy[J]. Pattern Recognit Lett, 1987,6(5):303-313.
  • 4P. Kovesi. Phase congruency detects comers and edges[C]//The Austra- lian Pattern Recognition Society Conference ,2003:309-318.
  • 5MORRONE M C,BURR D C.Feature detection in human vision: a phase-dependent energy model.[J].Proc R Soc Lond B Biol Sci,1988, 235(1280):221-45.
  • 6R. A. Owens, S. Venkatesh. On the classification of image features[J]. Pattern Recognition Letters, 1990,11: 339-349.
  • 7GRAESSER A C,WIEMER-HASTINGS K,WIEMER-HASTINGS P, et al.Autotutor: a simulation of a human tutor[J].Cogn Syst Res, 1999,1 (1):35-51.
  • 8D.J. Field. Relations between the statistics of natural images and the re- sponse properties of cortical cells[J]. Journal of the Optical Society of America, 1987, 4 (12): 2379-2394.

引证文献1

二级引证文献5

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部