应用相移技术和迭代算法的综合鉴别联合变换相关器

把相移技术和迭代算法应用到综合鉴别联合变换相关中,计算机模拟结果表明,运用了相移技术和迭代算法后这种相关器的光能效率和鉴别率得到了很大提高,实现了高鉴别率和高光能效率的综合鉴别光学模式识别.进一步研究了输入噪声对相关器性能的影响,相关的抗噪声能力有待提高.     

利用液晶光阀实现二值化联合变换相关器的研究

二值化联合变换相关器，通过对联合变换的功率谱进行二值化操作可以提高联合变换相关器的图像识别。本文正是基于此观点，首次提出利用液晶光阀本身的饱和区实现反转二值化联合变换功率谱。     

用于指纹识别的基于离散余弦变换的二值化联合变换相关器

提出了一种利用离散斜弦变换对联合功率谱进行处理的二值化联合变换相关算法,利用这种二值联合变换相关器,进行了一个待识别指纹同四个参考指纹的比较,这种相关器同采用局部中值阈值技术的二值化联合变换相关器相比,能提高输出峰边比,提高相关峰的强度。光电混合处理实验的结果表明,这种方法能大大提高多指纹识别系统的识别性能。     

二值化联合变换相关器的最佳阈值

从实验和计算机模拟两方面讨论二值化联合变换相关器的最佳阈值选取原则.实验研究表明,不同阈值对二值化联合变换相关结果有着较大影响,阈值过高或过低都会使联合变换相关结果变差.也就是说,二值化联合变换相关器存在一个最佳阈值.计算机模拟结果表明,最佳阈值位于联合变换功率谱的平均灰度值附近.在该阈值下,二值化联合变换相关器输出的相关峰值将相对提高,半宽度减小,同时噪音得到抑制.     

非准确联合变换相关

分析了联合变换相关中相关物或联合功率谱输入面偏离透镜前焦面的情况,或记录联合功率谱时透过两相关物的两相干光束间存在常数相位差时的情况,类似的非准确傅里叶变换被称为非准确联合变换相关。理论分析和实验验证表明,该种情况的相关点分布不变。     

基于双二次微分的联合变换相关识别

提出一种提高联合相关识别的有效方法，该方法通过对识别图像和联合变换功率谱分别进行二次微分，抽取识别图像的特征信息，增强联合变换功率谱中调制条纹的对比度和调制条纹的结构，有效地提高了联合变换相关器的相关输出；在此基础上，构造了基于双二次微分的１ｆ实时光电联合相关识别系统，实验结果表明：该方法较二元联合变换相关，提高了图像相关识别能力     

利用附加密钥旋转在光学联合相关结构中实现多二值图像加密EI北大核心CSCD

在一种改进的光学联合变换相关加密系统中,将附加密钥改为圆形并提出了基于附加密钥旋转复用而实现多幅二值图像加密的方法。加密时,对于不同的待加密的图像,将附加密钥旋转至不同的角度,生成相应的联合功率谱。将这些得到的联合功率谱进行叠加,得到的复合联合功率谱即最终的密文。解密时,将附加密钥旋转至加密时所处于的对应角度,对复合联合功率谱进行解密,即得到相应的解密结果。理论分析和计算机模拟结果表明,解密结果对附加密钥的旋转角度非常敏感,因而该旋转角度可作为一个有效的参数来实现多图像加密。同时,也分析了加密图像的数量对于解密结果的影响。     

光电混合光盘存储二值化联合变换相关器

本文提出了基于光盘存储的单空间光调制器光电混合联合变换相关系统,该系统采用视频光盘建立参考图象库,充分结合了联合变换相关器的内在优点和光盘系统的高信息存储能力,能实时地给出相关识别结果,是适合于机器人视觉的一种有效系统。文末给出了计算机模拟结果和初步的光学实验结果。     

非准确联合变换相关测量透镜焦距

提出了一种利用非准确联合变换相关测量透镜焦距的方法.该方法首先利用已知焦距透镜记录联合功率谱,再用记录的联合功率谱经被测焦距透镜输出相关点,记录相关点并测出其间距,可以计算出被测透镜的焦距.理论分析和实验结果表明,该方法有较高的测量准确度,能实现透镜焦距的自动测量.     

基于二值化调制度层析的快速在线三维测量算法

提出了一种基于二值化调制度层析的快速在线三维测量算法.对物体调制度信息进行层析分析,有效提取反映物体形状特征的层析信息,并将该双准确度层析信息进行二值化,以该二值化层析信息为模板,进行像素匹配,可实现快速在线三维测量.为验证该算法的可行性和有效性,进行了实物测试实验,该算法与提取调制度特征区域实现像素匹配的方法进行对比测试.实验表明,该算法具有很好的测量准确度,有效地调高了测量速度.     

Distortion-invariant pattern recognition using synthetic discriminant function based multiple phase-shifted-reference fringe-adjusted joint transform correlation

This paper proposes a novel pattern recognition system for invariance to noise and distortions. The technique first generates a synthetic discriminant function of the target image from its different distorted versions. It then takes four different phase-shifted versions of the reference image, which are individually joint transform correlated with the given input scene. Thus the proposed algorithm produces a single cross-correlation signal corresponding to each potential target. Also a fringe-adjusted filter is designed to generate a delta-like correlation peak with high discrimination between the signal and the noise. The pattern recognition system is also designed for the identification of multiple targets belonging to multiple reference objects simultaneously in a given input scene. The proposed technique is investigated using computer simulation including real-life images in different complex environments.     

Implementation of an algorithm for detecting patterns in defocused scenes using binary joint transform correlation

An original method to detect images in defocused scenes by means of a binary joint transform correlation is presented. Defocused images are described in frequency domain as the product between the Fourier transform of the in-focus scene by the optical transfer function of the imaging lens. This function, which presents positive and negative values, introduces sign errors in the joint power spectrum. The goal of this study is to detect the sign of the optical transfer function starting from the defocused image by means of a digital algorithm. Information provided by the algorithm allows to compensate the sign errors in the binary joint power spectrum and to obtain invariant correlations with respect to defocusing. Theoretical analysis and digital experiments to test the procedure are provided.     

Sliced orthogonal nonlinear generalized decomposition based fringe-adjusted joint transform correlation

A sliced orthogonal nonlinear generalized (SONG) decomposition based version of modified fringe-adjusted joint transform correlator (MFJTC), SBFJTC, is proposed. In SBFJTC scheme, the reference and input scenes are decomposed into a set of binary slices through SONG decomposition. MFJTC filtering of each pair of binary slices, corresponding to the same gray level of reference and input scene, is performed and then the outputs are added. Numerical simulations show that the proposed scheme delivers a better correlation performance and robustness to the white additive Gaussian noise, substitutive noise and nonoverlapping noise than that of both of the FJTC and the MFJTC.     

Spectral band independent recognition in a differential binary joint transform correlator

Images of a target in a specific spectral band in general show no correlation with images of the same target in a different spectral band. Hence in a joint transform correlator (JTC) architecture, if the reference and input target are the images captured through a visible (e.g., charge-coupled device or CCD camera) and infrared (IR) detector, autocorrelation peaks are not obtained. This drawback has been overcome in this paper by the use of a CCD–IR fused image as the reference image. Daubechies wavelet transform, which produces the least root-mean-square (RMS) error in the fusion process in comparison to other wavelets, has been used for the purpose. A comparative analysis of the proposed idea has been carried out for the classical JTC (CJTC), binary JTC (BJTC) and differential binary JTC (DBJTC) algorithms. Since the DBJTC removes the dc completely and produces sharp correlation peaks compared to the other techniques, computer simulation and experimental results are shown for the proposed idea using DBJTC. The same fused reference image has also been used to identify multiple targets in a scene using DBJTC. Performance measures like correlation peak intensity (CPI), dc/ac and peak correlation energy (PCE) have been calculated as metrics of goodness for the proposed scheme.     

Performance of an image-encrypted joint transform correlator for pattern recognition

An image-encrypted joint transform correlator for pattern recognition is proposed and evaluated. The correlator performs twofold correlation for recognizing the primary image and cipher, and the encrypting cipher acts to enhance or inhibit the correlation peak if the cipher is correctly input. By incorporating the original image with an appropriate cipher, the correlator achieves better pattern discrimination and is robust against distortion. Simulation results show that the pixel number and the cell size of cipher affect the characteristics of the correlator.     

多目标识别的联合变换相关器的研究

提出了一种可用于多目标识别的联合变换相关器。为改善相关信号的性能,对功率谱作了优化处理。为消除相关面上的零级项和目标间的相关项,可用联合功率谱减去纯目标输入的功率谱和参考图像的功率谱;为增强和锐化相关峰,将相减的功率谱作指数函数滤波处理。分析了指数滤波参数对相关结果的影响。计算机模拟结果表明,这种相关器所输出的相关信号比经典联合变换相关器和二元联合变换相关器输出的相关信号更好,互相关得到了抑制,自相关得到了增强,具有很好的抗噪能力。     

改进的对数联合变换相关器在噪声条件下的模式识别

对联合变换相关器的功率谱进行对数变换可强化其高频分量,锐化相关峰,但同时也会增强其噪声成分,影响抗噪性能。针对这一问题,提出了一种改进的对数联合变换相关器模型。通过改变对数函数形式来提高对数联合变换相关器的抗噪能力。计算机仿真结果表明,在附加高斯白噪声、非重叠低频和高频有色噪声的条件下,改进的对数联合变换相关器的抗噪能力均优于传统的对数联合变换相关器。     

Rotation-invariant pattern recognition using morphological fringe-adjusted joint transform correlation

We propose a rotation-invariant nonlinear correlator based on circular harmonic filter (CHF) and morphological Fringe-adjusted Joint Transform correlation (MFJTC). We refer to this correlator as a rotation-invariant MFJTC (RIMFJTC). Through computer simulation, we compare the output results of RIMFJTC with those of rotation-invariant MC (RIMC) and CHF when input scene is corrupted by salt-and-pepper noise, white additive Gaussian noise and cluttered background. Our results show that RIMFJTC yields higher discriminability, sharper and higher correlation peaks, and displays better stability against the above three kinds of noise than do the RIMC and common CHF.     

联合变换相关器像移测量试验系统设计

为了测量卫星姿态不稳定或振动等原因引起的空间相机亚像元像移,设计了基于联合变换相关器的像移测量试验系统。阐述了该方法的数学原理,面阵CCD的安装位置以及输入图像序列的获取方法。根据相关参数确定了试验系统的傅里叶透镜结构和参数,最终设计了试验系统。应用线性插值和像元合并方法获得具有亚像元像移的图像果表明,像移测量的精度不随景物的内容而变化,测量得到的像移误差均方根值<0.2pixel。