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.     

联合击中击不中变换相关器

将联合击中击 中变换相关器用于二值图像的目标识别。与常用的联合变换相关器相比，联合击中击不中变换相关器对联合变换相关器输入图像和参考图像进行互补编码。编码的目的在于通过联合变换相关器来一步实现形态学中的击中击不中变换。     

Image displacement based on phase-encoded reference joint fractional transform correlator

In order to utilize the space of an input plane efficiently and make the optical structure more flexible, an image displacement measurement based on phase-encoded reference joint fractional transform correlator (PER-JFrTC) is proposed. We use a random phase mask to encode the reference image and overlay it with the target image forming the input image. Joint power spectrum (JPS) of the input image is obtained by Fourier transform and the resultant is encoded by the same phase mask. Then a fractional Fourier transform with an order p is applied to the phase-encoded JPS (PJPS), resulting in a correlation output with a sharp cross-correlation peak, which includes the displacement information between the reference and the target image. Contrast to displacement measurement based on traditional joint transform correlator (JTC), PER-JFrTC can use the space of the input plane efficiently and reduces the influence of the auto-correlation. Also the position of cross-correlation peak can be fixed arbitrarily according to the fractional order p as well as the optical set-up can be more flexible and easier to implement. Results based on digital computation show that PER-JFrTC could detect the displacement accurately and verify our proposal. A possible optical set-up is suggested.     

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.     

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。     

Effect of dynamic range input image on performance of binary subtracted joint transform correlator

A demand for the dynamic range of input images in the binary subtracted joint transform correlator was studied by computer simulations using input scenes containing multiple halftone images of human faces. To realize good discriminability the correlator requires use of an image-conversion subsystem with a dynamic range larger than 50:1 and 16:1 in amplitude for input scenes having (1) a reference image and many target images and (2) a target image and many reference images, respectively.     

High-pass filtering and frequency spectrum correlation for larger size image recognition

A new method for larger size images recognition is proposed based on high-pass filtering and frequency spectrum correlation. The input images are first filtered by a high-pass filter. Then the filtered input images, which are overlapped rather than displaced from each other in the input plane, serve as the input images for frequency spectrum correlator. As a result, only one sharp correlation peak yields in the center of output plane when the target image matches with the reference image. More importantly, the method is especially suitable for larger size image recognition because of the input and correlation ways, which ensures better utilization of the space-bandwidth product and efficient utilization of the spatial light modulator and detector. Computer simulation results are presented to demonstrate the feasibility and effectiveness of this method.     

Improved approach for target detection and recognition on optoelectronic hybrid joint transform correlator

A conventional joint transform correlator (JTC) often generates large correlation sidelobes as well as a large correlation peak width, strong zero-order peak, and low diffraction efficiency in target detection and recognition, which make the detection ability of JTC lower. To conquer these difficulties, firstly, a joint power spectrum (JPS) subtraction technique was proposed in Fourier plane, where power spectrum of reference image and power spectrum of object image are subtracted from the JPS before inverse Fourier-transform operation, it is evident that the improved JPS removes the zero-order term. Secondly, a fringe-adjusted filter (FAF) was presented to restrain sidelobes and noises. The revised JPS is multiplied by a FAF before the inverse Fourier-transform operation to obtain the cross-correlation peak. Computer simulations showed the improved method can markedly eliminate zero-order diffraction and effectively control the sidelobes and noises compared to traditional JTC, and then enhance the detection ability for JTC. Experimental results presented the sharp correlation peak and also demonstrated this approach effectiveness.     

基于图像局部区域梯度特征描述的红外人体识别算法

提出了一种新的红外图像中人体目标识别方案并进行了算法实现。通过直方图聚类分析对红外图像进行分割,根据二值化图像团块的特点,确定图像中的候选目标图像区域。将候选目标图像按比例划分为多个区域,使用梯度位置朝向直方图(GLOH,Gradient location-orientation histogram)对候选目标图像进行描述。与其它红外图像中人体识别算法相比,不需要多种特征提取算法组合进行分步骤识别,仅使用单个SVM分类器即可达到满意的识别率,避免了分类器的级联,算法简单有效。     

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。     

Enhanced Optical Image Verification Based on Joint Transform Correlator Adopting Fourier Hologram

In this paper two new architectures for optical image verification are proposed. Both architectures are based on conventional joint transform correlators (JTCs) adopting a Fourier hologram and can significantly improve the recovered image quality. First, an input phase-only function is Fourier transformed and then interferes with a reference wave that is diffracted from a plane wave incident on another random phase mask. Second, two phase-only functions are placed at the two input sides of a beamsplitter such that the interference pattern of their Fourier transforms can be detected. To obtain a predefined target image in the output plane, one of the input phase functions is iteratively retrieved by the use of the projection onto constraint sets algorithm. Simulation results show that the less mean squared error and better image quality are obtained for both the binary and grayscale images.     

A New Quantum Gray-Scale Image Encoding Scheme

In this paper, a new quantum images encoding scheme is proposed. The proposed scheme mainly consists of four different encoding algorithms. The idea behind of the scheme is a binary key generated randomly for each pixel of the original image. Afterwards, the employed encoding algorithm is selected corresponding to the qubit pair of the generated randomized binary key. The security analysis of the proposed scheme proved its enhancement through both randomization of the generated binary image key and altering the gray-scale value of the image pixels using the qubits of randomized binary key. The simulation of the proposed scheme assures that the final encoded image could not be recognized visually. Moreover, the histogram diagram of encoded image is flatter than the original one. The Shannon entropies of the final encoded images are significantly higher than the original one, which indicates that the attacker can not gain any information about the encoded images.     

Composite wavelet based morphological correlation for continuous-scale-invariant pattern recognition

A composite nonlinear correlation is proposed to perform invariant recognition for the input image with continuous-scale distortions. The proposed correlation can be considered as a summation of many composite wavelet matched filters. Every matched filter consists of a linear combination of binary slices that are generated from threshold decomposition of the training images, and an adaptive wavelet filter. The adaptive wavelet is optimized to produce the sparse image features. Computer simulations are carried out to prove the scale-invariance and noise robustness of the new scheme.     

Binary phase only filters for rotation and scale invariant pattern recognition with the joint transform correlator

The joint transform correlator (JTC) is one of the two main optical image processing architecture which provides a highly effective way of comparing images in a wide range of applications. Traditionally, an optical correlator is used to compare an unknown input scene with a pre-captured reference image library, to detect if the reference occurs within the input. Strength of the correlation signal decreases rapidly as the input object rotates or varies in scale relative to the reference object. The aim of this paper is to overcome the intolerance of the JTC to rotation and scale changes in the target image. Many JTC systems are constructed with the use of ferroelectric liquid crystal (FLC) spatial light modulators (SLMs) as they provide fast two-dimensional binary modulation of coherent light. Due to the binary nature of the FLC SLMs used in the JTC systems, any image addressed to the device need to have some form of thresholding. Carefully thresholding the grey scale input plane and the joint power spectrum (JPS) has significant effect on the quality of correlation peaks and zero order (DC) noise. A new thresholding technique to binarise the JPS has been developed and implemented optically. This algorithm selectively enhances the desirable fringes in the JPS which provide correlation peaks of higher intensity. Zero order noise is further reduced when compared to existing thresholding techniques.Keeping in mind the architecture of the JTC and limitations of FLC SLMs, a new technique to design rotation and scale invariant binary phase only filters for the JTC architecture is presented. Filers design with this technique have limited dynamic range, higher discriminability among target and non-target objects, and convenience for implementation on FLC SLMs. Simulation and experiments shows excellent results of various rotation and scale invariant filters designed with this technique. A rotation invariant filter is needed for various machine vision applications of the JTC. By fixing the distance between camera and input object, the scale sensitivity of the correlator can be avoided. In contrast to the industrial machine vision applications, scale factor is very important factor for the applications of the JTC systems in defence and security. A security system using a scale invariant JTC will be able to detect a target object well in advance and will provide more time to take a decision.     

修正振幅调制的光电混合圆谐联合变换相关器作旋转不变的目标检测

提出一种修正振幅调制的光电混合圆谐联合变换相关器作旋转不变的目标检测的实验系统。参考图像（即圆谐展开分量的实部和虚部）、圆盘状的局部偏置函数以及目标图像同时显示于输入面。此方法对联合功率谱作了修正,先将联合功率谱减去纯输入景物（含局部偏置函数）的功率谱和参考图像（含局部偏置函数）的功率谱,再加上局部偏置函数的功率谱,然后将所得修正的联合功率谱乘以振幅调制滤波函数。这种方法能产生比普通的圆谐联合变换     

基于相位编码的畸变不变联合变换相关器的设计

采用综合鉴别函数(SDF)的方法合成几个子参考图象,用于解决畸变不变识别问题.通过相位编码技术和对联合功率谱的振幅调制,缩小了零级相关峰的宽度,锐化了相关峰,消除了多目标输入时各目标图象之间的互相关项和参考图象及各目标图象之间的共轭相关项,增强了对目标定位和识别的能力,最后给出计算机模拟结果.     

Polychromatic pattern recognition based on color component chaos encoding

In order to overcome the disadvantages which the single-channel system and the multichannel system suffer from some special cases, such as, when there exists a linear relationship between the corresponding color components of the target image and the reference image, a novel method for color pattern recognition is proposed based on color component chaos encoding. In this approach, the color components are first encoded into chaos images and then the encoded images serve as the input images of the single-channel (or multichannel) system. As a result, the color difference resulting from the linear relationship between the corresponding color components of the target image and the reference image can be recognized. Computer simulations prove that this method is valid.     

Extended fractional wavelet joint transform correlator

An extended fractional wavelet joint transform correlator is implemented for real-time target recognition applications. The real-time input scene captured using a charge-coupled device camera along with the reference image is fractional Fourier transformed. The obtained joint power spectrum is multiplied by an appropriately scaled wavelet filter and the resultant function is differentiated. The application of wavelet filter enhances the correlation outputs and differential processing of wavelet-filtered joint power spectrum improves the detection efficiency by reducing the zero-order spectra. Targets with Gaussian and speckle noise have also been used to check the correlation output. The performance metrics: correlation peak intensity, peak-to-correlation energy, peak-to-sidelobe ratio and signal to clutter ratio have been calculated. The experimental results are presented in support of the proposed idea.     

Hand vein recognition based on the connection lines of reference point and feature point

According to the essential characters of the image topology, a new hand vein recognition algorithm based on the connection lines of reference point and feature points is proposed. In this method, the intersection points and the endpoints of the vein image are used as feature points. After the intersection points and the endpoints selected as feature points, the reference point for image matching are extracted from these points. The relative distances between the reference point and the feature points and the angles between the adjacent connections of the reference point and feature points are calculated and used as recognition features. Finally these two features are combined for hand vein recognition. This method can effectively overcome the influence on the recognition results caused by image translation and rotation. Experimental results show that the proposed algorithm is able to achieve hand vein recognition reliably and quickly.     

基于Gabor小波变换的ICA火灾图像纹理识别算法

针对火灾图像纹理识别问题,提出了基于Gabor小波变换的ICA火灾图像纹理识别算法,并根据火灾图像纹理识别特点进行了优化。首先用不同尺度和方向的Gabor滤波器对待识别图像滤波,得到其特征图像,然后将特征图像转化成特征向量作为ICA的输入,得到基矢量子空间,再将测试图像经过Gabor滤波器的特征向量投影到ICA子空间中得到系数向量作为目标识别特征,最后用支持向量机进行识别。通过与Gabor滤波器法和ICA方法的对比实验,表明该算法可以在火灾纹理图像的识别率上比传统方法提高5%以上,为火灾图像识别提供了一种新思路。