一种图象中基元检测的新方法

在模式识别和机器视觉中，常常需要进行图象中的基元检测。本文以圆的检测为例提出了一种利用遗传算法进行基元检测的方法。实验结果表明，本文方法与通常的模板匹配和Ｈｏｕｇｈ变换相比速度大大提高。     

基于骨架特征的机场主跑道识别

基于骨架对跑道区域进行表示，从骨架图中检测骨架分支基元，计算分支基元的显著性度量并建立分支基元之间的邻接关系。针对机场跑道区域具有的几何特征，采用脊柱基元表示条状区域，将脊柱基元的宽度、长度和方向信息作为脊柱基元的显著性度量，借助先验知识，检测得到主跑道的脊柱基元，识别主跑道。选取一幅某机场遥感图像作为实验分析，验证了算法的可行性。     

二基元互谱定向有关问题研究

利用二基元或等效二基元分裂波束互谱定向是当前水声定向测量中普遍采用的技术方法,但存在工作带宽窄,检测空间范围小等问题。为扩大二基元互谱定向的应用范围,文章对分裂波束互谱定向的机理进行了探讨,分析了产生鉴向多值性的原因,研究了扩大空间定向范围的技术方法,探讨了提高二基元互谱定向精度的实现方法,并提出了扩大检测频率使用范围的技术途径,为今后分裂波束互谱定向得到更加广泛的应用打下良好的技术基础。     

电子探针定量分析中以高价氧化物为基元的α因子修正关系式

在氧化物体系(包括硅酸盐和其它含氧酸盐)的电子探针定量分析的α因子修正方法中,通常以低价氧化物和余额氧为基元进行计算,这在应用上有时并不方便。本文推导了以高价氧化物为计算基元的α因子修正关系式。在用此关系式对含有高价氧化物的试样进行分析时,可以直接得到高价基元氧化物的含量。对于有标样法和无标样联立方程法的计算,此关系式均可应用。高价基元氧化物的α因子值可从低价基元氧化物和余额氧的α因子值通过换算得到。文中列出了几种高价基元氧化物的计算α因子表。     

基于兴趣区检测的地面目标识别方法研究

提出了一种基于兴趣区检测的地面目标识别方法。根据目标模型的有关几何形状和热辐射知识，采用自上而下的计算模型，计算所提取的基元特征的显著性，并根据基元特征的显著性的大小确定出注视点及相应的兴趣区，然后对兴趣区中的图像进行分割，并利用模型知识对分割图像进行识别。该方法对已有的红外目标图像系列取得了很好的识别效果，提高了识别精度和弱小目标检测识别的能力。     

基于奇异值分解的快速直线提取方法

矩阵的奇异值分解能够反映矩阵数据的分布特征.利用数字图像中直线的结构特征,定义了近垂直直线基元和近水平直线基元,根据基元结构对边缘检测和细化后得到的线段进行扫描,将近似共线的点分别归入到若干个直线支撑点集合.对每个直线支撑点集合进行奇异值分解,利用得到的特征向量计算出其对应的Hough参数空间投票单元,实现对线段层次上...     

电子探针定量分析中以高价氧化物为基元的α因子修正关系式

在氧化体系 (包括硅酸盐和其它含氧酸盐 )的电子探针定量分析的α因子修正方法中 ,通常以低价氧化物和余额氧为基元 (或称端员 )进行计算 ,这在应用上有时并不方便。本文推导了以高价氧化物为计算基元的α因子修正关系式。用此关系式对含有高价氧化物的试样进行分析时 ,可以直接得到高价基元氧化物的含量。对于有标样法和无标样联立方程法的计算 ,此关系式均可应用。高价基元氧化物的α因子值可由低价基元氧化物和余额氧的α因子值通过换算而得到。氧化物体系 (包括硅酸盐和其它含氧酸盐 )电子探针定量分析的α因子修正法[1,2 ] ,由于如下原…     

克隆算子在民族图案生成中的应用研究

为了解决民族图案艺术得到传承和发扬的问题,提出了民族图案基元、民族图案元和民族图案再生元的概念。引进克隆算子对民族图案基元进行操作,并提出一种民族图案生成算法。利用本文提出的算法对民族图案的生成做实验,民族图案基元通过克隆操作、免疫基因操作、克隆选择操作和克隆死亡操作后能生成新的图案元。实验结果表明在继承图案民族内涵的情况下,能够生成新的民族图案元和再生图案元。利用本文提出的图案生成方法,可以为艺术设计者提供取之不尽的创新设计元素。     

几何基元的提取方法

基元提取在基于模型的计算机视觉中起着重要的作用。基元抽取问题可以归结为优化问题,即寻找代价函数的全局最小值。利用统计方法对最小子集进行随机抽样,大大减少了对最小子集的评价。同时引入了参数向量列表,并提出了一种新的代价函数,用于对基元的参数向量进行评价,使计算量减少、抽取精度提高。该方法可以用于多个基元的提取。分析实验结果表明,该方法能快速、准确地提取集合基元。     

汉语连续语音识别中不同基元声学模型的复合

该文研究由不同声学基元训练的声学模型的复合。在汉语连续语音识别中,流行的基元包括上下文相关的声韵母基元和音素基元。实验发现,有些汉语音节在声韵母模型下有更高的识别率,有些音节在音素模型下有更高的识别率。该文提出一种复合这两种声学模型的方法,一方面在识别过程中同时使用两种模型,另一方面在识别过程中避开造成低识别率的模型。实验表明,采用本文的方法后,音节错误率比音素模型和声韵母模型分别下降了9.60%和6.10%。     

Precise Geometric Registration of Aerial Imagery and LIDAR Data

In this paper, we develop a registration method to eliminate the geometric inconsistency between the stereo‐images and light detection and ranging (LIDAR) data obtained by an airborne multisensor system. This method consists of three steps: registration primitive extraction, correspondence establishment, and exterior orientation parameter (EOP) adjustment. As the primitives, we employ object points and linked edges from the stereo‐images and planar patches and intersection edges from the LIDAR data. After extracting these primitives, we establish the correspondence between them, being classified into vertical and horizontal groups. These corresponding pairs are simultaneously incorporated as stochastic constraints into aerial triangulation based on the bundle block adjustment. Finally, the EOPs of the images are adjusted to minimize the inconsistency. The results from the application of our method to real data demonstrate that the inconsistency between both data sets is significantly reduced from the range of 0.5 m to 2 m to less than 0.05 m. Hence, the results show that the proposed method is useful for the data fusion of aerial images and LIDAR data.     

Colour image retrieval based on primitives of colour moments

A colour image retrieval method based on the primitives of colour moments is proposed. First, an image is divided into several blocks. Then, the colour moments of all blocks are extracted and clustered into several classes. The mean moments of each class are considered as a primitive of the image. All primitives are used as features. Since two different images may have different numbers of features, a new similarity measure is then proposed. To demonstrate the effectiveness of the proposed method, two test databases from Corel are used to compare the performances of the proposed method with other existing ones. The experimental results show that the proposed method is usually better than the others. Furthermore, since for a few special types of images, other methods may have better results occasionally, a relevance feedback algorithm is also provided to automatically determine the best method according to the user's response.     

基于2D-PCA特征描述的非负权重邻域嵌入人脸超分辨率重建算法

在基于邻域嵌入人脸图像的超分辨率重建算法中,训练和重建均在特征空间进行,因此,特征选择对算法性能具有较大影响。另外,算法模型对重建权重未加限定,导致负数权重出现而产生过拟合效应,使得重建人脸图像质量衰退。考虑到人脸图像的特征选择以及权重符号限定的重要作用,该文提出一种基于2维主成分分析(2D- PCA)特征描述的非负权重邻域嵌入人脸超分辨率重建算法。首先将人脸图像分成若干子块,利用K均值聚类获得图像子块的局部视觉基元,并利用得到的局部视觉基元对图像子块分类。然后,利用2D-PCA对每一类人脸图像子块提取特征,并建立高、低分辨率样本库。最后,在重建过程中使用新的非负权重求解方法求取权重。仿真实验结果表明,相比其他基于邻域嵌入人脸超分辨率重建方法,所提算法可有效提高权重的稳定性,减少过拟合效应,其重建人脸图像具有较好的主客观质量。     

典型几何基元的高频散射建模方法梳理

高分辨率SAR图像中蕴含目标与环境丰富的信息,但复杂的电磁散射机制使其难以直观解译,这一直是SAR图像解译的重要研究课题.该文简单梳理了典型几何基元的高频散射建模方法,以面散射、线散射和点散射为线索简要回顾了若干高频散射机制的研究发展过程,并给出几种典型几何基元的散射机制表达式及部分仿真结果,分析了典型散射机制表征面临...     

Exploring visual dictionaries: A model driven perspective

Good representative dictionaries is the most critical part of the BoVW: Bag of Visual Words scheme, used for such tasks as category identification. The paradigm of learning dictionaries from datasets is by far the most widely used approach and there exists a plethora of methods to this effect. Dictionary learning methods demand abundant data, and when the amount of training data is limited, the quality of dictionaries and consequently the performance of BoVW methods suffer. A much less explored path for creating visual dictionaries starts from the knowledge of primitives in appearance models and creates families of parametric shape models. In this work, we develop shape models starting from a small number of primitives and develop a visual dictionary using various nonlinear operations and nonlinear combinations. Compared with the existing model-driven schemes, our method is able to represent and characterize images in various image understanding applications with competitive, and often better performance.     

Localized texture processing in vision: analysis and synthesis inthe Gaborian space

Recent studies of cortical simple cell function suggest that the primitives of image representation in vision have a wavelet form similar to Gabor elementary functions (EF's). It is shown that textures and fully-textured images can be practically decomposed into, and synthesized from, a finite set of EF's. Textured-images can be synthesized from a set of EF's using image coefficient library. Alternatively, texturing of contoured (cartoon-like) images is analogous to adding chromaticity information to contoured images. A method for texture discrimination and image segmentation using local features based on the Gabor approach is introduced. Features related to the EF's parameters provide efficient means for texture discrimination and classification. This method is invariant under rotation and translation. The performance of the classification appears to be robust with respect to noisy conditions. The results show an insensitivity of the discrimination to relatively high noise levels, comparable to the performances of the human observer.     

Automatic Contour Detection Using a "Fixed-Point Hachimura-Kuwahara Filter" for SPECT Attenuation Correction

Attenuation correction for single-photon emission computed tomography (SPECT) usually assumes a uniform attenuation distribution within the body surface contour. Previous methods to estimate this contour have used thresholding of a reconstructed section image. This method is often very sensitive to the selection of a threshold value, especially for nonuniform activity distributions within the body. We have proposed the "fixed-point Hachimura-Kuwahara filter" to extract contour primitives from SPECT images. The Hachimura-Kuwahara filter, which preserves edges but smoothes nonedge regions, is applied repeatedly to identify the invariant set-the fixed-point image-which is unchanged by this nonlinear, two-dimensional filtering operation. This image usually becomes a piecewise constant array. In order to detect the contour, the tracing algorithm based on the minimum distance connection criterion is applied to the extracted contour primitives. This procedure does not require choice of a threshold value in determining the contour. SPECT data from a water-filled elliptical phantom containing three sources was obtained and scattered projections were reconstructed. The automatic edge detection procedure was applied to the scattered window reconstruction, resulting in a reasonable outline of the phantom.     

Image coding with ridge and valley primitives

A high-compression image coding scheme is presented, based on thread-like “Ridge” and “Valley” primitives. The use of these primitives is motivated by their success in economically representing image structure. The original image is sampled along the primitives, using a fractal yardstick method to determine sample spacing. The primitives themselves are compressed using vector coding and chain coding. Reconstruction at the receiver is a scattered data interpolation problem, solved here using C⁰ natural neighbor interpolation. Results are presented showing data rates between 0.1 and 0.4 b/pixel, the degradations are discussed, and prospects for improvement outlined     

Ridge-based vessel segmentation in color images of the retina

A method is presented for automated segmentation of vessels in two-dimensional color images of the retina. This method can be used in computer analyses of retinal images, e.g., in automated screening for diabetic retinopathy. The system is based on extraction of image ridges, which coincide approximately with vessel centerlines. The ridges are used to compose primitives in the form of line elements. With the line elements an image is partitioned into patches by assigning each image pixel to the closest line element. Every line element constitutes a local coordinate frame for its corresponding patch. For every pixel, feature vectors are computed that make use of properties of the patches and the line elements. The feature vectors are classified using a kappaNN-classifier and sequential forward feature selection. The algorithm was tested on a database consisting of 40 manually labeled images. The method achieves an area under the receiver operating characteristic curve of 0.952. The method is compared with two recently published rule-based methods of Hoover et al. and Jiang et al. The results show that our method is significantly better than the two rule-based methods (p < 0.01). The accuracy of our method is 0.944 versus 0.947 for a second observer.