基于矢量夹角的三维物体识别

提出了一种基于局部描述符的物体识别算法.算法根据点云位置信息得到其矢量和曲率信息,根据形状索引提取特征点,在每个特征点根据矢量夹角把点云物体分割成不同的曲面片,每个矢量夹角曲面片通过一个二维直方图描述.该图显示了特征点与邻域之间法线矢量夹角对特征点法线矢量与特征点到邻域矢量之间夹角的出现频率.对于给定的一个物体,通过比对预测物体和模型物体的曲面片集描述,可得到潜在的对应模型物体,再通过迭代最近点算法,得到最终的识别结果.     

一种稳健的特征点配准算法

为了能准确快速提取特征和可靠匹配特征点对,提出一种稳健的基于特征点的配准算法。首先改进了Plessey角点检测算法,有效提高所提取特征点的速度和精度。然后利用相似测度归一化互相关(Normalized cross correlation,NCC),通过双向最大相关系数匹配的方法提取出初始特征点对,用随机采样符合法(Random sample consensus,RANSAC)来剔除伪特征点对,实现特征点对的精确匹配。最后用正确匹配特征点对实现图像的配准。实验表明,该方法能够快速准确地提取两幅图像间的对应特征点,大大降低了误匹配的概率,两幅图像光照不一致、重复性纹理、旋转角度比较大等较难自动匹配情形下,仍能有效地实现图像的配准。     

一种基于三角形几何结构的星图识别算法

提出了一种新的以星三角形为基本识别单元的几何结构星图识别算法。通过对观测误差的预处理,将该算法星三角形的匹配过程转换为一个没有误差的三角形识别问题。引入一个能部分描述三角形结构的特征量,将导航三角形的识别所需的特征匹配数量降低,而多三角形的组合有效地提高了正确识别率。仿真实验表明,该算法所需导航星库容量小,识别效率高,误识率低,实时性和鲁棒性优于传统的三角形星图识别算法。     

Good match exploration for thermal infrared face recognition based on YWF-SIFT with multi-scale fusion

Stable local feature detection is a critical prerequisite in the problem of infrared (IR) face recognition. Recently, Scale Invariant Feature Transform (SIFT) is introduced for feature detection in an infrared face frame, which is achieved by applying a simple and effective averaging window with SIFT termed as Y-styled Window Filter (YWF). However, the thermal IR face frame has an intrinsic characteristic such as lack of feature points (keypoints); therefore, the performance of the YWF-SIFT method will be inevitably influenced when it was used for IR face recognition. In this paper, we propose a novel method combining multi-scale fusion with YWF-SIFT to explore more good feature matches. The multi-scale fusion is performed on a thermal IR frame and a corresponding auxiliary visual frame generated from an off-the-shelf low-cost visual camera. The fused image is more informative, and typically contains much more stable features. Besides, the use of YWF-SIFT method enables us to establish feature correspondences more accurately. Quantitative experimental results demonstrate that our algorithm is able to significantly improve the quantity of feature points by approximately 38%. As a result, the performance of YWF-SIFT with multi-scale fusion is enhanced about 12% in infrared human face recognition.     

基于相似性度量的星系光谱红移估计

光谱的自动分析对大规模的光谱巡天有着非常重要的意义。文章提出了一种基于相似性度量的星系光谱红移测量方法。方法中采用主分量分析构造星系光谱的静止模板,利用谱线特征确定观测光谱的红移候选,然后根据红移候选进行观测光谱与模板光谱间的相似性度量,所采取的相似性度量策略类似于证据积累的思想,定义为几个相似证据的加权和,从而降低了观测光谱与模板光谱之间的误匹配,提高了红移估计的正确率。通过实验将所提出方法与基于谱线匹配的方法和传统的交叉相关方法进行了比较,实验结果表明：本文方法的正确率较之基于谱线匹配的方法和传统相关法有较大提高。     

基于自适应粒子群算法的多峰谱线分离方法研究

电感耦合等离子体原子发射光谱分析法（ICP-AES）已成为一种常规的元素分析方法,但在ICP-AES分析过程中,大多元素的分析谱线会受到背景或其他谱线的重叠干扰,形成的光谱干扰严重影响了谱线分析的准确性,所以在元素的分析过程中,需要通过适当的光谱干扰校正方法才能得到合适的元素分析线。根据光谱强度具有叠加性的特征,利用谱图将谱线形状表示为Voigt线型函数加和的多峰谱线叠加模型,以多峰谱线叠加模型与目标谱线的均方根误差构建多元函数作为评价函数的数学模型,设计自适应粒子群优化（APSO）算法寻找分离谱线特征参数的最优解,APSO算法在标准PSO算法的基础上,引入压缩因子同时使得种群参数惯性权重根据粒子个体适应度值自适应变化以及学习因子线性变化,在算法迭代过程中协调粒子种群内全局搜索能力和局部开发能力,保证算法有效且迅速收敛,实现多峰谱线分离,减少干扰谱线的影响从而得到更精准的元素分析线。以ICP-AES检测器返回的含Pr元素溶液特征波长为390.844 nm和汞灯特征波长为313.183 nm两条谱线的光强AD采样值作为两组实测数据,以两个Voigt线型近似函数构成的三种不同重叠程度的叠加合成曲线作为三组模拟数据,在数据曲线上分别选取50个能够包含曲线全部特征参数信息的点作为数据点,通过对上述五组目标数据点进行APSO算法处理,结果表明APSO算法得到的多峰谱线叠加模型相关参数能够较准确地拟合出相应的目标数据曲线,目标数据点与拟合曲线函数值相对误差较低,算法表明能够有效扣除谱线重叠干扰,同组目标数据经过多次算法处理,选择最小的最优适应度值相应的特征参数向量作为Voigt线型函数相关参数,以此拟合出的多峰谱线叠加模型曲线精准度越高、相对误差越小。这种算法具有良好的收敛性和适应性,可应用于ICP-AES在元素定性、定量方面的分析研究。     

Registration and integration algorithm in structured light three-dimensional scanning based on scale-invariant feature matching of multi-source images

Based on the homography between a multi-source image and three-dimensional (3D) measurement points, this letter proposes a novel 3D registration and integration method based on scale-invariant feature matching. The matching relationships of two-dimensional (2D) texture gray images and two-and-a-half- dimensional (2.5D) range images are constructed using the scale-invariant feature transform algorithms. Then, at least three non-collinear 3D measurement points corresponding to image feature points are used to achieve a registration relationship accurately. According to the index of overlapping images and the local 3D border search method, multi-view registration data are rapidly and accurately integrated. Experimental results on real models demonstrate that the algorithm is robust and effective.     

利用共线性和对极约束实现匹配扩展

结构化场景图像的纹理较为单一,可提取的局部特征较少。在宽基线情况下,基于图像局部特征的匹配方法很难获取正确匹配,导致匹配精度降低。为此,提出了一种以图像局部特征匹配为基础进行配扩展的方法。匹配扩展时,将图像中线段的两端点作为匹配的基元,利用线段两端点在不同视点间的共线性和对极约束限定候选匹配的搜索空间,剔除错误匹配,进行匹配关系的传播。实验结果表明:当图像存在一定的尺度和视点变化以及明显的光照变化时,该方法能够有效地增加匹配的数目,为精确的极线几何估计和三维重建奠定了良好的基础。     

尺度不变特征与几何特征融合的人耳识别方法

要提高人耳的识别率,关键是特征的提取与表达.尺度不变特征变换(SIFT)技术是局部点特征提取算法,在尺度空间寻找极值点,提取对图像的尺度和旋转变化具有不变性,对光照变化和图像变形具有较强的适应性的特征向量.尝试用SIFT技术来提取外耳图像的结构特征点以形成稳定的特征描述子,为了克服一幅图像中有多个局部描述子相似的问题,在SIFT特征描述子中融入一个耳廓几何特征.最后采用特征向量的欧氏距离作为两幅图像相似性度量标准进行人耳识别.在耳图像库七进行实验.结果表明,该方法不仅可以有效地提取人耳特征,通过少量特征可获得较高的识别率,而且对耳图像刚体变化具有较强的稳健性.     

Estimation of forced-selection word intelligibility by comparing objective distances between candidates

We proposed and evaluated an estimation method for the forced selection speech intelligibility tests. Our proposal takes into account the forced selection manner of the Diagnostic Rhyme Test (DRT), which forces selection from a pair of rhyming words. A distance measure is calculated between the test word and the two candidate words, respectively, and the distance is compared to select the most likely word. We compared two distance measures. The first objective distance measure used here was based on the Articulation index Band Correlation (ABC). The ABC is the correlation of time–frequency (T–F) patterns between the test word and the template word speech of the two words in the candidate word pair. The word with the higher correlation was decided to be the likely candidate word. The T–F pattern was calculated in the Articulation Index (AI) bands, and the correlation was calculated between the corresponding bands of the test and candidate word sample. In order to estimate the intelligibility, we calculate the ratio of the number of bands in which higher correlation is seen for the correct word vs. the total number of bands (named ABC-est). This ratio quantifies how well the test word matches the correct word in the word pair. For the second objective distance, we used a measure based on the frequency-weighted segmental SNR (fwSNR_seg). Segmental SNR (SNR_seg) was calculated in AI bands, and compared among the candidate word templates. We then calculated the frequency-weighted ratio of the number of bands in which higher SNR_seg was observed for the correct word vs. the total number of bands (named fwSNR_seg-est), again to quantify how well the test word matches the selected candidate word in the pair. We estimated a logistic mapping function from the above two ratios to intelligibility scores using speech mixed with known noise. The mapping functions were then used to estimate the intelligibility of speech mixed with unknown noise. This estimation was compared to another measure that we previously evaluated, the conventional fwSNR_seg, which directly maps the measure to intelligibility. Both proposed measures were proven to be significantly more accurate than conventional fwSNR_seg. For most cases, the accuracy was comparable between the two proposed distance measures, ABC-est and fwSNR_seg-est, with the latter showing correlation between the subjective and estimated intelligibility as high as 0.97, and root mean square as low as 0.11 for one of the test sets, but not as accurate for other sets. The ABC-est showed more stable accuracy for all sets. However, both measures show practical accuracies in all conditions tested. Thus, it should be possible to “screen” the intelligibility in many of the noise conditions to be tested, and cut down on the scale of the subjective test needed.     

基于SIFT特征区域的抗几何攻击图像水印算法

提出了一种基于局部特征区域的抗几何攻击图像水印算法.首先利用尺度不变特征变换在载体图像的尺度空间上提取特征点并形成特征区域,该区域具有缩放、平移不变性;然后通过主方向归一化,使这些区域具有旋转不变性;最后将水印信息重复嵌入到多个不重叠的局部特征区域的DFT中频系数中.仿真结果表明,该算法在获得较好的不可见性的同时,对几何攻击和常规信号处理均具有良好的鲁棒性.     

基于自归一化神经网络的脉冲星候选体选择

脉冲星候选体选择是脉冲星搜寻任务中的重要步骤.为了提高脉冲星候选体选择的准确率,提出了一种基于自归一化神经网络的候选体选择方法.该方法采用自归一化神经网络、遗传算法、合成少数类过采样这三种技术提升对脉冲星候选体的筛选能力.利用自归一化神经网络的自归一化性质克服了深层神经网络训练中梯度消失和爆炸的问题,大大加快了训练速度.为了消除样本数据的冗余性,利用遗传算法对脉冲星候选体的样本特征进行选择,得到了最优特征子集.针对数据中真实脉冲星样本数极少带来的严重类不平衡性,采用合成少数类过采样技术生成脉冲星候选体样本,降低了类不平衡率.以分类精度为评价指标,在3个脉冲星候选体数据集上的实验结果表明,本文提出的方法能有效提升脉冲星候选体选择的性能.     

AKAZE结合自适应局部仿射匹配的视差图像特征匹配算法

针对常用的图像特征匹配算法对具有视差的图像在图像特征匹配阶段会产生大量误匹配点的问题,提出了一种AKAZE（accelerated-KAZE）算法结合自适应局部仿射匹配的特征匹配算法。首先,采用AKAZE算法提取特征点;接着,采用二进制描述符M-LDB(modified-local difference binary)进行描述并进行暴力匹配产生粗匹配点对;最后,基于图像的仿射变换可以提供较强的几何约束这一特性,采用自适应局部仿射匹配完成精匹配。实验结果表明,该算法针对具有旋转变化、尺度变化、视角变化的图像匹配,具有提取特征点均匀、匹配准确等效果,提取的正确特征点数量分别平均相对于SIFT算法提升了1.66倍、SURF算法提升了1.08倍、ORB算法提升了6.92倍、GMS算法提升了1.23倍,能够满足具有较大视差图像匹配的需求。     

改进SIFT变换与客观评价结合的图像配准算法

针对SIFT(Scale Invariant Feature Transform)算子在大幅复杂图像中提取的过多不稳定特征点及在只有少量重合区域下图像配准过程中出现的过多误匹配,导致图像配准精度下降。提出一种改进的SIFT算法,在对目标图像提取SIFT特征后,利用双向BBF(Best-Bin-First)匹配算法对提取的特征点进行匹配,采用SIFT描述子的尺度以及梯度方向信息建立最小邻域匹配剔除误匹配点,通过随机抽取一致性算法(RANSAC)进一步筛选匹配点,并利用最小二乘法结合多项式近似拟合出变换模型,利用局部均方根有效值(RMS)评价映射矩阵与实际图像的误差,找出并删除引起误差的误匹配点,迭代至配准图像符合评价标准后,计算出精确变换模型。实验结果表明,该算法提高了大幅复杂图像在少量重合区域时的配准精度。     

Pose measurement method based on geometrical constraints

The pose estimation method based on geometric constraints is studied.The coordinates of the five feature points in the camera coordinate system are calculated to obtain the pose of an object on the basis of the geometric constraints formed by the connective lines of the feature points and the coordinates of the feature points on the CCD image plane;during the solution process,the scaling and orthography projection model is used to approximate the perspective projection model.The initial values of the coordinates of the five feature points in the camera coordinate system are obtained to ensure the accuracy and convergence rate of the non-linear algorithm.In accordance with the perspective projection characteristics of the circular feature landmarks,we propose an approach that enables the iterative acquisition of accurate target poses through the correction of the perspective projection coordinates of the circular feature landmark centers.Experimental results show that the translation positioning accuracy reaches ±0.05 mm in the measurement range of 0-40 mm,and the rotation positioning accuracy reaches ±0.06° in the measurement range of 4°-60°.     

电子稳像的特征点跟踪算法

提出一种利用特征跟踪进行电子稳像的算法,该算法具有计算量小,精度高,有鲁棒性等优点。算法由两部分构成:(1)基于特征点集二维运动模型进行全局运动估计。提取图像的特征点,以其为中心建立特征窗进行块匹配,得到匹配特征点集,根据特征点集内具有稳定相对位置的结构特征,提出距离不变准则,对特征匹配进行验证,以保证各点的局部运动具有良好的全局一致性,从而形成特征点集的全局运动矢量;(2)利用自适应均值滤波去除摄像机抖动。均值滤波器可以有效平滑摄像机的高频抖动,同时滤波器尺寸自适应地根据抖动频率来调整大小,能够防止过稳或欠稳。实验结果表明,该算法能够有效减轻摄像机的旋转和平移抖动。     

Feature points extraction of different structure for industrial computed tomography image contour

In order to accurately obtain the physical structure and dimension, the feature points extraction must be carried out from the ICT (industrial computed tomography) image contour. Therefore, the discrete data could be transformed into CAD models, and different methods have been developed for the feature points extraction, according to geometric features, the function and shape of mechanical parts. We discussed the feature points extraction methods, and one method is not enough to all the structures, so we must first distinguish the structure as regular and irregular. For the regular structures, by using a positive–negative factor, the curvature estimation method was improved. This method was designed and verified for the actual part, and has an improved accuracy in the feature points extraction. While for the irregular structures we used the polygon approximation method in the feature points extraction. For a complex part composing of several regular structures and irregular structures in the same ICT contour, we divided the whole contour into the regular and irregular structures, then used the corresponding methods for each structure. Last all feature points were extracted. The actual examples showed that the used methods are practical and effective.     

Multifractal properties of aperiodic Ising model on hierarchical lattices: role of the geometric fluctuations

The role of the geometric fluctuations on the multifractal properties of the local magnetization of aperiodic ferromagnetic Ising models on hierarchical lattices is investigated. The geometric fluctuations are introduced by generalized Fibonacci sequences. The local magnetization is evaluated via an exact recurrent procedure encompassing real space renormalization group decimation. The symmetries of the local magnetization patterns induced by the aperiodic couplings is found to be strongly (weakly) different, with respect to the ones of the corresponding homogeneous systems, when the geometric fluctuations are relevant (irrelevant) to change the critical properties of the system. At the criticality, the measure defined by the local magnetization is found to exhibit a non-trivial F(α) spectra being shifted to higher values of α when relevant geometric fluctuations are considered. The critical exponents are found to be related with some special points of the F(α) function and agree with previous results obtained by the quite distinct transfer matrix approach. Received 2 April 2001 and Received in final form 14 August 2001     

Geometrically robust image watermarking using scale-invariant feature transform and Zernike moments

In order to resist geometric attacks, a robust image watermarking algorithm is proposed using scaleinvariant feature transform (SIFT) and Zernike moments. As SIFT features are invariant to rotation and scaling, we employ SIFT to extract feature points. Then circular patches are generated using the most robust points. An invariant watermark is generated from each circular patch based on Zernike moments.The watermark is embedded into multiple patches for resisting locally cropping attacks. Experimental results show that the proposed scheme is robust to both geometric attacks and signal processing attacks.     

基于非采样Contourlet变换高分辨率遥感图像配准

为了提高高分辨率遥感图像配准的精确度,将非采样Contourlet变换应用于高分辨率遥感图像配准算法中.首先对高分辨率遥感图像进行非采样Contourlet变换.利用非采样Contourlet变换的平移不变性在变换域提取图像的边缘并选择合适的阈值准确地得到图像的边缘特征点.然后利用归一化互相关匹配法和概率支撑法对特征点进行匹配.最后通过三角形局部变换映射甬数实现图像配准.实验结果表明,该方法更能准确地提取高分辨率遥感图像的特征点,大大提高了正确匹配的概率,与基于小波方法的图像配准效果相比有更高的准确性和稳健性.