空间频率通道中噪声对体视匹配的影响

本工作希望了解噪声在各空间频率通道中对体视的影响.产生从5%至35%每隔5%的七个等级的随机点噪声图象,参照Wilson四通道模型的频率分别用两种不同滤波器对随机点立体图对(RDS)及噪声图象进行滤波,然后在各通道图对中加入不同通道噪声进行匹配观察.得到:1.高频通道的体视抗干扰能力高于低频通道.2.Gabor函数滤波后图对的体视抗干扰能力高于Butterworth滤波器滤波后的,但均低于未滤波的.3.当噪声大于15%时,低频噪声对低频图对及高频噪声对高、低频图对的体视匹配有抑制作用,而低频噪声对高频图对则影响很小.4.未滤波及各通道图对的最大噪声容限均不超过25%.     

不同滤波方法对超声图像分割的影响

采用各向异性滤波方法以及Gabor滤波方法对乳腺肿瘤超声图像进行处理,再使用snake方法以及levelset方法在设置相同参数的条件下,对过滤的图像分别进行分割。试验结果表明,不同的滤波方法在分害4目标图像的收敛度,边缘圆滑度及整体轮廓提取效果都有较大影响,为分割图像选取适当的滤波器提供了参考。     

线画图形质地辨认的一个神经网络模型

本文提出了一个能辨认线画质地的神经网络模型,并在IBM-PC机上对它进行了成功的模拟.该模型可与真实的视觉系统建立起很好的对应关系,因此可以认为它是对视觉系统质地辨认过程的一个机器再现.另外,本文推广了原广义Gabor函数模型,得到了一个适合于描写网络层次视觉功能的单细胞感受野的数学描述.     

视觉系统初级信息处理的时变通带滤波模型

通过分析在视觉初级信息处理过程中时间、空间信息的依存关系,提出了随时间变化的方差σ＾２（ｔ）因子表示的时变通带高斯滤波函数模型,从数学上证明了时变带通高斯函数的微分正好实现了空间域中的滤波,由此分别讨论了零交叉检测滤波器和典型的ｏｎ－ｏｆｆ感受野的关系,计算了各特征频率通道的峰值频率,该值在一定程度上与以往的研究结果基本吻合。本文从数学上具体描述了视觉信息的提取过程是一个分时分频的提取过程的思想,     

视觉图象-背景相对运动分辨模型

在蝇视觉相对运动神经计算原理的基础上,提出一个新的视觉图象-背景相对运动分辨模型.它包括(1)视觉图象-背景相对运动分辨的初级视觉加工,即运动图象的滤波加工;(2)视觉图象-背景相对运动分辨的中级视觉加工,即滤波器输出的运动图象与亮度边缘信息的平行整合加工.考虑到传统的计算机是串行加工方式,难以实时处理信息量巨大的运动目标图象,而且计算的原理与神经计算有着根本区别,建立了一个生物学似真的实时运动信息加工神经网络电子装置,在此装置上对模型进行检验,实现了目标图象与复杂的背景图象的实时高分辨率相对运动分辨.提出视觉残象在运动图象滤波中起着重要作用;运动视觉的孔径问题应分成两部分来处理:孔径问题引起的运动图象与背景分离不完整的问题,通过视觉的多通道信息的平行整合能得到较好的解决,而孔径问题引起的速度方向测不准在视觉整合中只能得到一定的补偿。     

基于FPGA 超声信号数字动态滤波器的实现

目的:本文研究了基于现场可编程门阵列(Field Programmable Gate Array,FPGA)超声成像系统中数字动态滤波器的实现方法和过程。方法:动态滤波器中FIR滤波器采用分布式算法(Distributed Arithmetic,DA)实现结构,并在应用中对DA算法进行了改进,包括数据并行处理结构的设计、对查找表(Look Up Table,LUT)输入字长N大小的控制和具有对称系数的FIR滤波器的采用。改进后的DA实现在FPGA资源占用和处理速度之间达到了平衡。同时,结合多级流水线结构,动态滤波器实现了数字超声信号并行处理。结果:采用常值滤波器(远场匹配参数)进行滤波后,超声回波图像远场分辨率达到了要求,但越靠近近场效果越差。相比之下,本文设计的基于FPGA超声信号动态数字滤波器达到了很好的滤波效果,使回声图像近场和远场都有最佳分辨率。结论:利用FPGA实现超声系统中动态滤波器是完全可行的,并且有助于提高系统的稳定性和可靠性,并大大减低系统成本。     

基于Gabor滤波器的皮肤纹理图像增强

在疗效化妆品中,常常需要对护肤品的性能和效果进行分析。皮肤纹理的检测是客观衡量疗效化妆品的有效手段。基于计算机视觉技术的皮肤纹理分析,对拍摄的皮肤图像要进行图像预处理,增强图像,为后续的分析提供有效的数据。采用经过微调的定向的Gabor滤波器进行增强图像,通过实验得出Gabor滤波器不仅抑制噪声的效果好,还保留了皮肤图像的整体和局部特征。     

一种基于视网膜主血管方向的视盘定位及提取方法

为分割出眼底图像中的视盘,构建基于眼底图像的计算机辅助诊断系统,提出了一种基于视网膜主血管方向的视盘定位及提取方法。首先,利用Otsu阈值分割眼底图像R通道获取视盘候选区域;然后利用彩色眼底图像的HSV空间的H通道提取视网膜主血管并确定主血管方向;在此基础上,通过在方向图内寻找出对加权匹配滤波器响应值最高的点确定视盘中心位置;最后,利用该位置信息从视盘候选区域中"挑选"出真正的视盘。利用该方法对100幅不同颜色、不同亮度的眼底图像进行视盘分割,得到准确率98%,平均每幅图像处理时间1.3 s。结果表明:该方法稳定可靠,能快速、有效分割出眼底图像中的视盘。     

用数量场描述方向敏感感受野

1965年Barlow ＆ Levick及我国科技工作者分别独立提出了原理大致相同的方向检测感受野模型,但其数学模型却一直未见有报道.本文用数量场方法给出了其数学模型,这是一个Gabor函数模型,并据此解释了方向检测感受野的方向调谐曲线以及方向检测通道数量问题.     

视觉运动图象滤波模型及其实时模拟

在充满生存竞争的动物世界,视觉的伪装与反伪装现象随处可见,视觉反伪装的原理是什么？本文对Ｒｅｉｃｈａｒｄｔ的图形－背景相对运动分辨模型加以发展,提出了视觉反伪装功能的运动图象滤波器模型。为了检验此模型,我们建立了一个生物学似真的实时运动信息加工神经网络电子装置,实现了实时、高分辨运动目标图象滤波。与Ｍｅａｄ的人工视网膜的运动目标图象检测功能相比,检测的运动目标图象的分辨率有很大提高,而噪声水平显著降低,克服了人工视网膜的一些局限性。     

Stereo disparity computation using Gabor filters

A solution to the correspondence problem for stereopsis is proposed using the differences in the complex phase of local spatial frequency components. One-dimensional spatial Gabor filters (Gabor 1946; Marcelja 1980), at different positions and spatial frequencies are convolved with each member of a stereo pair. The difference between the complex phase at corresponding points in the two images is used to find the stereo disparity. Disparity values are combined across spatial frequencies for each image location. Three-dimensional depth maps have been computed from real images under standard lighting conditions, as well as from random-dot stereograms (Julesz 1971). The algorithm can discriminate disparities significantly smaller than the width of a pixel. It is possible that a similar mechanism might be used in the human visual system.     

Detection of aperiodic test patterns by pattern specific detectors revealed by subthreshold summation

The hypothesis that the visual system detects, under certain conditions, stimulus patterns by means of filters matched to these patterns (Hauske et al. 1976) may be challenged by the argument that other coding mechanisms like spatial frequency channels, Gabor or Hermite filters mimick the behaviour of matched filters, a view supported by the finding of non-linear contrast-interrelationship functions (CIFs), as determined in superposition experiments. In this paper we argue that an overall non-linear CIF does not contradict the hypothesis of detection by a single matched filter: we find that the sensitivity functions determined in our experiments can be separated into two components reflecting (i) a bandpass filter and (ii) a filter characterised by the spectrum of the test-pattern. Received: 16 December 1996 / Accepted in revised form: 9 June 1998     

A Bayesian model of stereopsis depth and motion direction discrimination

 The extraction of stereoscopic depth from retinal disparity, and motion direction from two-frame kinematograms, requires the solution of a correspondence problem. In previous psychophysical work [Read and Eagle (2000) Vision Res 40: 3345–3358], we compared the performance of the human stereopsis and motion systems with correlated and anti-correlated stimuli. We found that, although the two systems performed similarly for narrow-band stimuli, broad-band anti-correlated kinematograms produced a strong perception of reversed motion, whereas the stereograms appeared merely rivalrous. I now model these psychophysical data with a computational model of the correspondence problem based on the known properties of visual cortical cells. Noisy retinal images are filtered through a set of Fourier channels tuned to different spatial frequencies and orientations. Within each channel, a Bayesian analysis incorporating a prior preference for small disparities is used to assess the probability of each possible match. Finally, information from the different channels is combined to arrive at a judgement of stimulus disparity. Each model system – stereopsis and motion – has two free parameters: the amount of noise they are subject to, and the strength of their preference for small disparities. By adjusting these parameters independently for each system, qualitative matches are produced to psychophysical data, for both correlated and anti-correlated stimuli, across a range of spatial frequency and orientation bandwidths. The motion model is found to require much higher noise levels and a weaker preference for small disparities. This makes the motion model more tolerant of poor-quality reverse-direction false matches encountered with anti-correlated stimuli, matching the strong perception of reversed motion that humans experience with these stimuli. In contrast, the lower noise level and tighter prior preference used with the stereopsis model means that it performs close to chance with anti-correlated stimuli, in accordance with human psychophysics. Thus, the key features of the experimental data can be reproduced assuming that the motion system experiences more effective noise than the stereoscopy system and imposes a less stringent preference for small disparities. Received: 2 March 2001 / Accepted in revised form: 5 July 2001     

Gabor Filter Optimization Design for Iris Texture Analysis

1　IntroductionIrisrecognitiontechniqueisbasedonthestableanddistinctiveirispatterns,andhasattractedmuchat tentionofsomeexpertsforthelastfewdecades .Sincethe 1990’s ,muchworkonirisrecognitionhasbeendoneandgreatprogresshasbeenmade[1- 4] .Nowadaysithasbecomeamostimportantbiometricsolutionforpersonalidentification .Anirishasanapproximatelycircularannularshape.Theiristexturehasarandomlydistributedstructureofdetails ,whichiscreatedbyradialandcon centricfurrows,pigmentspots,crypts ,pigmentfrillandc…     

Energy filters,motion uncertainty,and motion sensitive cells in the visual cortex: a mathematical analysis

Energy filters are tuned to space-time frequency orientations. In order to compute velocity it is necessary to use a collection of filters, each tuned to a different space-time frequency. Here we analyze, in a probabilistic framework, the properties of the motion uncertainty. Its lower bound, which can be explicitly computed through the Cramér-Rao inequality, will have different values depending on the filter parameters. We show for the Gabor filter that, in order to minimize the motion uncertainty, the spatial and temporal filter sizes cannot be arbitrarily chosen; they are only allowed to vary over a limited range of values such that the temporal filter bandwidth is larger than the spatial bandwidth. This property is shared by motion sensitive cells in the primary visual cortex of the cat, which are known to be direction selective and are tuned to spacetime frequency orientations. We conjecture that these cells have larger temporal bandwidth relative to their spatial bandwidth because they compute velocity with maximum efficiency, that is, with a minimum motion uncertainty.     

A scheme for binocular depth perception suggested by neurophysiological evidence

A scheme suggested by neurophysiological evidence is proposed to account for the perceptual phenomena related to binocular stereopsis, especially those observed with Julesz' random stereograms. In the scheme, monocular local features are extracted first. Then the correspondence between the left and right local features is searched for. The correspondence is not one-to-one in general. Thus a sort of direction column due to Blakemore is formed. Each unit in the column is binocular and the receptive field belonging to one eye is located in the same part of the visual field as long as the unit belongs to the same column. However, the receptive fields belonging to the other eye are horizontally displaced to one another. That is, each unit is characterized by binocular disparity. If the correspondence is not one-to-one, then several units belonging to the same column respond simultaneously. Binocular stereopsis can be established if one-to-one correspondence is determined to yield global three dimensional regions. The determination of one-to-one correspondence is carried out through a sort of laterally interacting circuitry in the disparity domain. After the determination of local correspondence, three dimensional global regions are formed by detecting the boundary and by filling-in occluded regions. The results of computer simulation are presented regarding Julesz' stereograms with various types of perturbation. Furthermore, the case of random-dot stereogram in which there is a size difference between the left and right images is simulated. Finally, the computer simulation related to the hysteresis in binocular depth perception is carried out.     

Configuration effects on texture transparency

This study examined the factors producing the perception of transparency between overlaid regions composed of Gabor micro-patterns as functions of their spatial frequency, separation of overlaid regions, and types of orientation modulation. The results showed that the likelihood of perceiving transparency was high both when (1) the difference in Gabor spatial frequency between regions was large, and (2) the region boundary, which was formed by short-range orientation differences in the Gabor micro-patterns, clearly emerged. We conclude that texture transparency appears to result from an interaction between a boundary-detection mechanism defining the shape of each region and a surface-detection mechanism assigning the boundary.     

Gabor filters as texture discriminator

The present paper presents a model for texture discrimination based on Gabor functions. In this model the Gabor power spectrum of the micropatterns corresponding to different textures is calculated. A function that measures the difference between the spectrum of two micropatterns is introduced and its values are correlated with human performance in preattentive detection tasks. In addition, a two stage algorithm for texture segregation is presented. In the first stage the input image is transformed via Gabor filters into a representation image that allows discrimination between features by means of intensity differences. In the second stage the borders between areas of different textures are found using a Laplacian of Gaussian operator. This algorithm is sensitive to energy differences, rotation and spatial frequency and is insensitive to local translation. The model was tested by means of several simulations and was found to be in good correlation with known psychophysical characteristics as texton based texture segregation and micropattern density sensitivity. However, this simple model fails to predict human performance in discrimination tasks based on differences in the density of terminators. In this case human performance is better than expected.