一种广义正交不变图像矩:雅可比-傅立叶矩

提出一种多畸变不变的正交图像矩:雅可比-傅立叶矩.其核函数由径向雅可比多项式和角向傅立叶复指数因子组成.雅可比多项式中的两个参数p和q的变化能够形成各种正交多项式,因而形成各种正交图像矩:勒让德-傅立叶矩(p＝1,q＝1)、切比雪夫-傅立叶矩(p＝2,q＝3/2)、正交傅立叶-梅林矩(p＝2,q＝2)和Zernike矩以及变形Zemike矩,等等.因此雅可比-傅立叶矩是核函数由径向多项式和角向傅立叶复指数因子组成的正交图像矩的一般形式,为这种正交图像矩的数学分析和优化提供了理论基础.     

Radial Tchebichef moment invariants for image recognition

Radial Tchebichef moments as discrete orthogonal moments in the polar coordinate have been successfully used in the field of image recognition. However, the scale invariant property of these moments has not been studied due to its complexity of the problem. In this paper, we present a method to construct a set of scale and rotation invariants extracted from radial Tchebichef moments, named radial Tchebichef moment invariants (RTMI). Experimental results show the efficiency and the robustness to noise of the proposed method for recognition tasks.     

基于不变距的舰船目标识别

通过对Hu不变矩和仿射不变矩原理的分析,得知不变距特征在图像平移、伸缩、旋转时均保持不变.分析了舰船红外图像的特点,结合Hu不变矩和仿射不变距原理,以大量外场试验数据为基础,对转向的舰船进行了识别研究.从仿真实验得到的大量数据中,发现舰船在转向过程中仍然能很好的识别.     

Video hashing with secondary frames and invariant moments

Video hashing is a useful technique of many multimedia systems, such as video copy detection, video authentication, tampering localization, video retrieval, and anti-privacy search. In this paper, we propose a novel video hashing with secondary frames and invariant moments. An important contribution is the secondary frame construction with 3D discrete wavelet transform, which can reach initial data compression and robustness against noise and compression. In addition, since invariant moments are robust and discriminative features, hash generation based on invariant moments extracted from secondary frames can ensure good classification of the proposed video hashing. Extensive experiments on 8300 videos are conducted to validate efficiency of the proposed video hashing. The results show that the proposed video hashing can resist many digital operations and has good discrimination. Performance comparisons with some state-of-the-art algorithms illustrate that the proposed video hashing outperforms the compared algorithms in classification in terms of receiver operating characteristic results.     

广义雅可比-傅立叶矩

图像正交矩具有数值稳定和方便重构等优点,雅 可比-傅立叶矩(JFM)是传统正交矩的推广,然而其定义中 的径向函数仅是整数阶多项式。本文改造JFM的径向函数,提出广义JFM,其定 义中的径向函数既可以是分数阶的多项式,也可以是更一般的函数,JFM仅是这种构造的特 例,并且证明了所提广义JFM的正交性和旋转不变性。数值实验也表明,利用所 提方法可构造出重构性能好、抗噪性能强的图像正交矩。     

基于Zernike矩的低信噪比红外目标检测方法

针对低信噪比红外目标图像,分析了Zernike矩的基本原理、计算方法和旋转不变性,提出了基于Zernike正交矩的低信噪比红外目标检测方法,并比较了模板匹配、Hu矩、Zernike矩方法的目标识别效果.理论分析与实验验证了所提方法的有效性.     

激光CCD自准直仪圆目标中心抗噪声精确定位方法

为满足高精度计量和方位瞄准跟踪系统的发展对激光CCD自准直仪测量精度的要求,提出一种基于正交傅里叶-梅林矩的激光CCD自准直仪圆目标中心抗噪声精确定位方法。首先利用正交傅里叶-梅林矩(OFMM)的幅值旋转不变性和更低径向矩阶数在充分提取图像边缘细节信息的同时抑制图像噪声的影响,通过对图像边缘旋转后垂直方向上不同阶次的正交傅里叶-梅林矩之间关系的分析将圆目标轮廓定位至亚像素级,然后采用最小二乘拟合方法实现圆目标中心的精确定位。结果表明,该方法稳定性好,定位精度高且抗干扰能力强,改进后的激光CCD自准直仪的测量分辨力提高了10倍,测量精度由2″提高到±0.18″,可有效满足在小角度测量和瞄准等领域的高精度测量需要。     

时间正交Gaussian-Hermite矩的性质及其应用

矩早已被广泛地应用于模式识别、图像处理、计算机视觉和多分辨分析中.取高斯函数作平滑核的时间正交Gaussian-Hermite矩是最近才提出来的信号处理的数学工具.在这篇文章中,我们首先给出时间正交Gaussian-Hermite矩的一些时一频性质.为了克服运动目标检测的传统方法的不足,我们提出一种基于正交Gaussian-Hermite矩的运动目标检测方法.最后给出了此方法和其它运动目标检测方法的实验对比结果;实验表明,我们的方法是有效的.     

Legendre矩的两种快速算法

Legendre正交矩在模式识别、图像分析等许多领域都有成功的应用,但是由于其计算的复杂性,相关的快速算法的研究尚未得到很好的解决.本文针对一类采用图像块方法描述的图像,提出两种快速、有效的计算Legendre矩的新方法,它们分别是累加方法和积分方法.这两种方法都有效地降低了计算复杂度,缩短了计算时间.     

Target recognition in SAR images using radial Chebyshev moments

In this study, a new algorithm for classification of ground vehicles from standard synthetic aperture radar (SAR) images is proposed. Radial Chebyshev moment (RCM) is a discrete orthogonal moment that has distinctive advantages over other moments for feature extraction. Unlike invariant moments, its orthogonal basis leads to having minimum information redundancy, and its discrete characteristics explore some benefits over Zernike moments (ZM) due to having no numerical errors and no computational complexity owing to normalization. In this context, we propose to use RCM as the feature extraction mechanism on the segmented image and to compare results of the fused images with both Zernike and radial Chebyshev moments. Firstly, by applying different threshold target and shadow parts of each SAR images are extracted separately. Then, segmented images are fused based on the combination of the extracted segmented region, segmented boundary and segmented texture. Experimental results will verify that accuracy of RCM, which improves significantly over the ZM. Ten percent improvement in the accuracy is obtained by using RCM and fusion of segmented target and shadow parts. Furthermore, feature fusion improves the total accuracy of the classification as high as 6%.     

基于修正不变矩和范数的物体特征识别方法

为了快速而准确地识别出不同类的物体,提出基于修正不变矩和最小范数的物体识别方法,提取物体的不变矩和圆形度特征,利用泛函分析中的范数理论对不同形状的物体进行识别,方法简单,识别速度快,并且识别率较高.仿真结果表明该方法对物体的平移、旋转、缩放都具有不变性,从而验证了该方法的有效性.     

融合图像轮廓矩和傅立叶描叙子的手势识别

针对手势识别中人手是复杂变形体,手部特征描叙容易受到环境因素影响的特点,提出了一种基于混合轮廓特征的手势识别的新方法.首先根据手的颜色信息将手从复杂的背景中分离出来,然后提取出手轮廓的矩不变量和Fourier描叙子特征,然后将2种特征融合构成混合特征,最后将新特征输入BP神经网络进行识别.实验表明:此方法具有较好的鲁棒性和较高的识别率.     

多重不变图象特征抽取器

提出一种光电混合图象特征抽取器。特征抽取器从Ｈｏｕｇｈ变换数据中实时地抽取满足图象移动、转动与尺度缩放多重不变性的９个图象几何特征量和不变矩特征量，模拟实验证实了９个特征量的多重不变性。     

采用径向Tchebichef矩不变量的飞机型号识别

针对几何矩非正交性对目标描述的不足以及连续正交矩在处理数字图像方面存在离散化误差的缺陷,为了提高识别精度,提出了一种利用离散正交的Tchebichef矩结合全局特征和局部特征的飞机型号识别方法。首先,根据几何矩和Tchebichef矩之间的关系,利用归一化几何中心矩、圆谐函数得到径向Tchebichef矩的旋转、尺度和平移(RST)不变量;然后,利用径向Tchebichef矩提取飞机目标的局部和全局特征构成特征向量;最后,利用Matlab构造了四类飞机的样本集,采用支持向量机(SVM)作为分类器识别测试样本飞机型号,分析了几何矩、Zernike矩和本文方法在识别精度上的差异以及训练样本集大小对识别精度的影响。实验结果表明,本文提出的算法提高了识别精度,并且在训练样本集较小时仍能获得90%以上的识别精度。     

Robust image hash in Radon transform domain for authentication

Image authentication has become an emergency issue in the digital world as it can be easily tampered with the image editing techniques. In this paper, a novel robust hashing method for image authentication is proposed. The reported scheme first performs Radon transform (RT) on the image, and calculates the moment features which are invariant to translation and scaling in the projection space. Then discrete Fourier transform (DFT) is applied on the moment features to resist rotation. Finally, the magnitude of the significant DFT coefficients is normalized and quantized as the image hash bits. Experimental results show that the proposed algorithm can tolerate almost all the typical image processing manipulations, including JPEG compression, geometric distortion, blur, addition of noise, and enhancement. Compared with other approaches in the literature, the reported method is more effective for image authentication in terms of detection performance and the hash size.     

基于Tchebichef不变矩的多比特抗几何攻击图像盲水印算法

现有的大多数水印算法对旋转、平移和尺度变换等几何攻击的鲁棒性比较差,微小的几何攻击都有能导致水印检测器失效,因此水印算法对几何攻击具有鲁棒性非常重要。本文提出了一种基于Tchebichef不变矩实现的多比特几何攻击不变性图像盲水印算法。文中具体介绍了Tchebichef不变矩的构造方法,水印是事先产生的与原始图像无关的信号,嵌入过程中将水印嵌入到图像的Tchebichef不变矩中实现几何攻击不变性。水印检测过程中采用独立分量分析技术实现真正意义上的多比特水印盲检测。文中具体分析了所提出的水印算法的计算复杂度,实验过程中采用通用水印测试软件Stirmark对所提出的水印算法进行鲁棒性测试,实验数据说明这种水印算法对Stirmark具有很好的鲁棒性。