基于蛙眼R3细胞感受野模型的运动滤波方法

李智勇; 何霜; 刘俊敏; 李仁发

doi:10.16383/j.aas.2015.c140810

基于蛙眼R3细胞感受野模型的运动滤波方法

doi: 10.16383/j.aas.2015.c140810

1.
湖南大学信息科学与工程学院嵌入式与网络计算湖南省重点实验室长沙 410082

基金项目:

国家高技术研究发展计划(863计划) (2012AA01A301-01),国家自然科学基金(91320103), 广东省省部产学研结合项目(2012A090300003),广东省科技计划项目(2013B090700003)资助

详细信息

作者简介:
何霜湖南大学信息科学与工程学院硕士研究生. 2012 年获得湖南商学院学士学位. 主要研究方向为图像处理, 运动目标跟踪.E-mail: heshuang@hnu.edu.cn

通讯作者:
李智勇湖南大学教授. 主要研究方向为动态多目标优化, 量子进化计算, 图像理解与视觉认知计算. E-mail: zhiyong.li@hnu.edu.cn

计量
- 文章访问数: 1708
- HTML全文浏览量: 100
- PDF下载量: 1314
- 被引次数: 0
出版历程
- 收稿日期: 2014-11-25
- 修回日期: 2015-01-19
- 刊出日期: 2015-05-20

Motion Filtering by Modelling R3 Cell's Receptive Field in Frog Eyes

1.
College of Computer Science and Electronic Engineering, Hunan University, Embedded and Network Computing Key Laboratory in Hunan Province, Changsha 410082

Funds:

Supported by National High Technology Research and Development Program of China (863 Program) (2012AA01A301-01), National Natural Science Foundation of China (91320103), Special Project on the Integration of Industry, Education and Research of Guangdong Province (2012A090300003), and Science and Technology Planning Project of Guangdong Province (2013B090700003)

摘要

摘要: 视觉感受野(Visual receptive field)模型作为生物视觉感知计算的基础单元,在整个生物视觉信息加工过程中发挥着重要作用.借鉴具有运动视觉特长的生物感受野特性研究高效的运动视觉计算技术,是一种潜在可行的方法.本文基于蛙眼R3细胞感受野,在高斯差分模型(Difference of Gaussians, DOG)的基础上引入时间和空间各向异性的运动视觉表达方式, 提出一种基于蛙眼R3细胞的不对称各向异性感受野(Asymmetric anisotropy receptive field, AARF)模型,表达蛙类视觉系统对运动目标敏感的视觉时空特征.基于该运动视觉模型,进一步提出了一种面向序列图像运动目标分析的蛙眼时空运动滤波算子(Frog-based spatio-temporal motion filter, FSTMF),以实现运动目标准确检测与分析.实验结果表明,该方法具有使序列图像背景模糊、动态目标突显的滤波效果,既符合蛙眼视觉背景模糊而前景清晰的特性,也为下一步运动目标的准确检测实现了高效的预处理.
- 蛙眼视觉特性 /
- 不对称各向异性 /
- 感受野模型 /
- 蛙眼时空运动滤波分析
Abstract: As a basic unit of biological visual perception computing, the visual receptive field plays a significant role in the whole process of biological visual information processing. It is a potentially feasible method for further study of efficient computing technology based on motion visual characteristic from biological receptive field. Inspired by frog eye's R3 cell receptive field, this study introduces a spatio-temporal anisotropy motion visual presentation to the difference of Gaussians (DOG) model. Thus, an asymmetric anisotropy receptive field (AARF) model is presented. This model can express frog visual system's spatio-temporal characteristic which is sensitive to moving visual targets. Based on the motion visual model, a frog-based spatio-temporal motion filter (FSTMF) is further proposed, which aims at accurate moving object detection and analysis in sequential images and videos. The experimental results demonstrate that the proposed method can obscure the background and highlight the moving targets. It is in accordance with frog eye's vision features with background vagueness and foreground clearness. Meanwhile, the filtering method can be as efficient pre-processing for accurate detection of moving objects.
- Frog visual characteristic /
- asymmetric anisotropy /
- receptive field model /
- frog-based spatio-temporal motion filter (FSTMF)

HTML全文

参考文献(21)

[1]	Zhang Zhen, Chen Zhe, Lv Li, Wang Xin, Xu Li-Zhong. Adaptive background suppression method based on visual receptive field. Chinese Journal of Scientific Instrument, 2014, 35(1): 191-199(张振, 陈哲, 吕莉, 王鑫, 徐立中. 基于视觉感受野的自适应背景抑制方法. 仪器仪表学报, 2014, 35(1): 191-199)
[2]	[2] Lee Y. A Neural Network Model of Frog Retina: A Discrete Time-Space Approach. Massachusetts Amherst: University of Massachusetts Amherst, 1986, 10: 415-426
[3]	[3] Nishio K, Yonezu H, Furukawa Y. Analog integrated circuit for motion detection with simple-shape recognition based on frog vision system. Optical Review, 2007, 14(5): 271-281
[4]	Zhao Liang, Wang Tian-Zhen, Liu Yong-Hong. Research on frog visual behavior and its computer simulation. Journal of Wuhan University of Technology (Information Management Engineering), 2003, 25(4): 1-5(赵亮, 王天珍, 刘永红. 青蛙视觉行为与计算机模拟概述. 武汉理工大学学报(信息与管理工程版), 2003, 25(4): 1-5)
[5]	Wang Zhi-Ling, Chen Zong-Hai, Xu Xiao-Xiao, Wu Liang. A fuzzy region understanding tactic for object tracking based on frog's vision characteristic. Acta Automatica Sinica, 2009, 35(8): 1048-1054(王智灵, 陈宗海, 徐萧萧, 吴亮. 基于蛙眼视觉特性的运动目标模糊化区域理解跟踪方法. 自动化学报, 2009, 35(8): 1048-1054)
[6]	[6] Xiao S S, Gao N. Research on visual invariance based on dynamic receptive field. In: Proceedings of the 2008 International Conference on Computer Science and Software Engineering. Wuhan, China: IEEE, 2008, 1: 273-276
[7]	[7] Zhang P. Extracting visual saliency based on multi-scale receptive field template. In: Proceedings of the 2nd International Conference on Digital Manufacturing and Automation (ICDMA). Zhangjiajie, China: IEEE, 2011. 527-530
[8]	[8] Ekvall S, Kragic D. Receptive field cooccurrence histograms for object detection. In: Proceedings of the 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems. Edmonton, Alberta, Canada: IEEE, 2005. 84-89
[9]	[9] Perez C A, Salinas C A, Estevez P A, Valenzuela P M. Genetic design of biologically inspired receptive fields for neural pattern recognition. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 2003, 33(2): 258-270
[10]	Yang B, Zhao Q Y, Zhang R, Yin B L. Receptive field based image modeling method for interactive segmentation. In: Proceedings of the 2nd International Congress on Image and Signal Processing. Tianjin, China: IEEE, 2009. 1-4
[11]	Lee D H, Lee J J. Incremental receptive field weighted actor-critic. IEEE Transactions on Industrial Informatics, 2013, 9(1): 62-71
[12]	Lettvin J Y, Maturana H R, Mcculloch W S, Pitts W H. What the frog's eye tells the frog's brain. Proceedings of the IRE, 1959, 47(11): 1940-1951
[13]	Hoshino N, Matsumoto N. Intracellular analysis of directional sensitivity of tectal neurons of the frog. Brain Research, 2003, 966(2): 185-193
[14]	Li Xiao-Ping, Bian Zhao-Qi, Wang Yun-Jiu. An efficient algorithm for the implementation of a 2D Gabor filtering. Acta Automatica Sinica, 1989, 15(2): 136-141(李小平, 边肇祺, 汪云九. 二维Gabor滤波器的快速实现. 自动化学报, 1989, 15(2): 136-141)
[15]	Li Xiao-Lei, Ma Miao. Contour detection based on combination of LoG filters method. Computer Technology and Development, 2014, (11): 28-31(李晓磊, 马苗. 基于组合LoG滤波方法的轮廓检测. 计算机技术与发展, 2014, (11): 28-31)
[16]	Chen Xiao-Hong. Research on Touchscreen Glass Defects Detection Methods Based on Computer Vision [Master dissertation]. South China University of Technology, China, 2013.(陈晓红. 基于机器视觉的触摸屏玻璃缺陷检测方法研究[硕士学位论文], 华南理工大学, 中国, 2013.)
[17]	Zhou Bo, Qian Kun, Ma Xu-Dong, Dai Xian-Zhong. A new nonlinear set membership filter based on guaranteed bounding ellipsoid algorithm. Acta Automatica Sinica, 2013, 39(2): 150-158)(周波, 钱堃, 马旭东, 戴先中. 一种新的基于保证定界椭球算法的非线性集员滤波器. 自动化学报, 2013, 39(2): 150-158)
[18]	Zhao Lin, Wang Xiao-Xu, Sun Ming, Ding Ji-Cheng, Yan Chao. Adaptive UKF filtering algorithm based on maximum a posterior estimation and exponential weighting. Acta Automatica Sinica, 2010, 36(7): 1007-1019(赵琳, 王小旭, 孙明, 丁继成, 闫超. 基于极大后验估计和指数加权的自适应UKF滤波算法. 自动化学报, 2010, 36(7): 1007-1019)
[19]	Zhang Gui-Mei, Zhang Song, Chu Jun. A new object detection algorithm using local contour features. Acta Automatica Sinica, 2014, 40(10): 2346-2355(张桂梅, 张松, 储珺. 一种新的基于局部轮廓特征的目标检测方法. 自动化学报, 2014, 40(10): 2346-2355)
[20]	Chen C Y, Zhao M Y. Video segmentation algorithm based on improved kirsch edge operator and three-frame difference. Advanced Materials Research, 2014, 981: 335-339
[21]	Agaian S S, Silver B, Panetta K A. Transform coefficient histogram-based image enhancement algorithms using contrast entropy. IEEE Transactions on Image Processing, 2007, 16(3): 741-758

施引文献

资源附件(0)

访问统计

计量

文章访问数: 1708
HTML全文浏览量: 100
PDF下载量: 1314
被引次数: 0

姓名
邮箱
手机号码
标题
留言内容
验证码

留言板

基于蛙眼R3细胞感受野模型的运动滤波方法

doi: 10.16383/j.aas.2015.c140810

作者简介:
何霜湖南大学信息科学与工程学院硕士研究生. 2012 年获得湖南商学院学士学位. 主要研究方向为图像处理, 运动目标跟踪.E-mail: heshuang@hnu.edu.cn

通讯作者:
李智勇湖南大学教授. 主要研究方向为动态多目标优化, 量子进化计算, 图像理解与视觉认知计算. E-mail: zhiyong.li@hnu.edu.cn

计量

Motion Filtering by Modelling R3 Cell's Receptive Field in Frog Eyes

计量

目录

留言板

基于蛙眼R3细胞感受野模型的运动滤波方法

doi: 10.16383/j.aas.2015.c140810

作者简介: 何霜湖 南大学信息科学与工程学院硕士研究生. 2012 年获得湖南商学院学士学位. 主要研究方向为图像处理, 运动目标跟踪.E-mail: heshuang@hnu.edu.cn

通讯作者: 李智勇 湖南大学教授. 主要研究方向为动态多目标优化, 量子进化计算, 图像理解与视觉认知计算. E-mail: zhiyong.li@hnu.edu.cn

计量

出版历程

Motion Filtering by Modelling R3 Cell's Receptive Field in Frog Eyes

计量

出版历程

目录

作者简介:
何霜湖南大学信息科学与工程学院硕士研究生. 2012 年获得湖南商学院学士学位. 主要研究方向为图像处理, 运动目标跟踪.E-mail: heshuang@hnu.edu.cn

通讯作者:
李智勇湖南大学教授. 主要研究方向为动态多目标优化, 量子进化计算, 图像理解与视觉认知计算. E-mail: zhiyong.li@hnu.edu.cn