Non-Uniform Sampling and Hardware Design of the Bionic Vision Method

您当前的位置：

首页 >

文章列表页 >

Non-Uniform Sampling and Hardware Design of the Bionic Vision Method

更新时间：2025-07-09

- Non-Uniform Sampling and Hardware Design of the Bionic Vision Method
- Vol. 44, Issue 6, Pages: 99-103(2010)
- 作者机构：
  
  西安交通大学人工智能与机器人研究所,西安,710049
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP391
- Online First：10 June 2010，
  
  Published：2010
- 稿件说明：
移动端阅览
Non-Uniform Sampling and Hardware Design of the Bionic Vision Method[J]. 2010, 44(6): 99-103.
DOI：

Non-Uniform Sampling and Hardware Design of the Bionic Vision Method[J]. 2010, 44(6): 99-103. DOI：

摘要

利用生物的选择注意机制可减少计算量的优势

提出了仿生物视觉的非均匀采样方法并实现了硬件设计.利用基于高斯函数的模型模拟了生物视觉的选择性响应特性

由此得到采样层优先和采样密度优先的2种非均匀采样表达式.在视觉处理芯片中

根据人眼特性并利用采样密度优先的方法

将图像分为4层进行非均匀采样和数据传送.实验表明:较之已有的非均匀采样方法

所提方法更具生物视觉特性和物理可实现性

并具有较高的压缩率; 当注视点为图像中心时

数据压缩率达到了 1/28; 利用任意选取注视点得到的非均匀采样数据恢复的图像效果符合人眼视觉特性.

Abstract

The usage of biological vision selective attention mechanism(VSAM)is important in the vision research

and can reduce the computing data. A non-uniform sampling method of bionic vision is designed and implemented. A Gaussian function-based model is proposed from the analysis of the selective response characteristics of biological vision

and two non-uniform sampling expressions are obtained based on the priority of sampling layer and the priority of sampling density. According to characteristics of human eye

four non-uniform sample layers are carried out in images by the second expression

and the proposed sampling method is implemented in our self-designed vision chip. Experiment results and comparisons with existing non-uniform sampling methods show that the proposed method has the biological visual characteristics and hardware realization with a high compression ratio. The compression ratio reaches 1/28 when the focus point is in the image center

and the images restored from the non-uniform sampling data are in line with the VSAM of human eye.

关键词

Keywords

references

郑南宁. 计算机视觉与模式识别[M].北京: 国防工业出版社, 1998.

DAVIES E R. Machine vision: theory, algorithms, practicalities [M]. 3rd ed. Singapore:Elsevier, 2009.

MEI Kuizhi, ZHANG Bing, GE Chenyang. A hierarchical and parallel SoC architecture for vision processor [J]. IEICE Electronics Express, 2009,6(19):1380-1386.

BOLDUC M, LEVINE M D. A review of biologically-motivated space-variant data reduction models for robotic vision [J]. Computer Vision and Image Understanding,1998,69(2):170-184.

SANDINI G, QUESTA P, SCHEFFER D,et al. A retina-like CMOS sensor and its applications [C]∥Proceedings of the 2000 IEEE Sensor Array and Multichannel Signal Processing Workshop. Piscataway, NJ, USA: IEEE, 2000:514-519.

李奇, 冯华君, 徐之海. 自动对焦系统中图像非均匀采样的实验研究 [J].光子学报, 2003, 32(12): 1499-1501.

LI Qi, FENG Huajun, XU Zhihai. Autofocus system experiment study using variational image-sampling [J]. Acta Photonica Sinica, 2003, 32(12): 1499-1501.

訾方, 李言俊, 张科, 等. 矩形非均匀采样算法和对数极坐标变换算法的比较分析 [J]. 计算机应用, 2007, 27(7):1619-1622.

ZI Fang, LI Yanjun, ZHANG Ke, et al. Comparative analysis on rectangular non-uniform sampling algorithm and log-polar transformation algorithm of image [J]. Computer Applications, 2007, 27(7):1619-1622.

RODIECK R W. Quantitative analysis of cat retinal ganglion cell response to visual stimuli [J].Vision Research, 1965, 5(11):583-601.

全局重建和位置块残差补偿的人脸图像超分辨率算法.西安交通大学学报, 2010, 44(4): 9-12.

利用粒子群优化的人脸特征提取识别算法.西安交通大学学报, 2010, 44(4): 48-51.

面向多源知识融合的扩展主题图相似性算法.西安交通大学学报, 2010, 44(2): 20-24.

一维子空间的三维重建方法.西安交通大学学报, 2009, 43(12): 31-34.

一种适合漫反射表面从明暗恢复形状的快速算法.西安交通大学学报, 2009, 43(10): 7-11.

基于特征层和二代曲波变换的多模生物特征融合识别方法.西安交通大学学报, 2009, 43(10): 32-36.

利用单幅影像的空间目标姿态测定方法.西安交通大学学报, 2009, 43(9): 56-61.

一种从明暗恢复形状的快速黏性解算法.西安交通大学学报, 2009, 43(6): 43-47.

人眼视觉特性与粗糙集结合的X射线图像增强算法.西安交通大学学报, 2009, 43(6): 48-51.

三维子空间约束的遮挡点恢复方法.西安交通大学学报, 2009, 43(4): 10-13.

一种Log-Gabor滤波器结合多分辨率分析的虹膜识别方法.西安交通大学学报, 2009, 43(4): 31-33.

利用贫富差距原理进行图像边缘检测.西安交通大学学报, 2009, 43(4): 44-48.

透视投影下的镜面反射表面形状恢复新算法.西安交通大学学报, 2009, 43(2): 6-9.

求积分卡尔曼粒子滤波算法.西安交通大学学报, 2009, 43(2): 25-28.

一种轮廓变化图像小波矩的步态识别.西安交通大学学报, 2009, 43(1): 90-94.

一种基于分辨函数的属性约简算法及其应用.西安交通大学学报, 2008, 42(12): 1455-1458.

一种无需匹配的多目重构方法.西安交通大学学报, 2008, 42(12): 1476-1480.

一种八叉树编码加速的3D纹理体绘制算法.西安交通大学学报, 2008, 42(12): 1490-1494.

采用二代曲波变换和反向传播神经网络的人脸识别方法.西安交通大学学报, 2008, 42(10): 1213-1216.

一种Roberts 自适应边缘检测方法.西安交通大学学报, 2008, 42(10): 1240-1244.

带多局部形状参数的三次扩展均匀B样条曲线.西安交通大学学报, 2008, 42(10): 1245-1249.

自适应估计模糊参数的最大后验概率超分辨率复原算法.西安交通大学学报, 2008, 42(10): 1254-1258.

基于等高线的图像特征表达.西安交通大学学报, 2008, 42(4): 385-388.

二阶中心差分粒子滤波算法.西安交通大学学报, 2008, 42(4): 409-413.

一种由明暗恢复形状的改进变分算法.西安交通大学学报, 2008, 42(4): 418-422.

一种基于虹膜和人脸的多生物特征融合方法.西安交通大学学报, 2008, 42(2): 133-137.

质心迭代图像跟踪算法.西安交通大学学报, 2007, 41(12): 1396-1400.

基于球体追踪的动态视差遮挡映射算法.西安交通大学学报, 2007, 41(12): 1401-1405.

一种有效抑制睫毛干扰的虹膜定位算法.西安交通大学学报, 2007, 41(10): 1175-1178.

一种针对非均匀有理B样条曲面的碰撞检测算法.西安交通大学学报, 2007, 41(4): 389-392.

基于直方图偏差约束的快速模糊C均值图像分割法.西安交通大学学报, 2007, 41(4): 430-434.

基于二维条码的指纹特征信息隐藏方法研究.西安交通大学学报, 2007, 41(2): 145-148.

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Sensitivity Analysis of Foil Geometrical Parameters for the Third-Generation CO2 Gas Foil Bearings Based on Design of Experiments Method

Effects of Expansion Angle Crater Film Hole on the Film Cooling Characteristics of a Double-Wall Structure

Numerical Simulation of the Energy Conversion Process in Thermoacoustic Engines with Different Stack Materials

Effects of Steam Addition on the Swirl Combustion and Emission Characteristics of Cracked Ammonia

Review of the Application of EBSILON Software in Combined Heat and Power System Optimization

Related Author

No data

Related Institution

No data

⁰