Perspective-aware texture analysis and synthesis

This paper presents a novel texture synthesis scheme for anisotropic 2D textures based on perspective feature analysis and energy optimization. Given an example texture, the synthesis process starts with analyzing the texel (TEXture ELement) scale variations to obtain the perspective map (scale map). Feature mask and simple user-assisted scale extraction operations including slant and tilt angles assignment and scale value editing are applied. The scale map represents the global variations of the texel scales in the sample texture. Then, we extend 2D texture optimization techniques to synthesize these kinds of perspectively featured textures. The non-parametric texture optimization approach is integrated with histogram matching, which forces the global statics of the texel scale variations of the synthesized texture to match those of the example. We also demonstrate that our method is well-suited for image completion of a perspectively featured texture region in a digital photo.     

基于条块拼接的快速纹理合成

针对离线纹理合成算法所生成纹理占用较多存储空间的问题,提出一种所生成纹理可紧凑保存的快速纹理合成算法.该算法相继沿垂直和水平方向以条块拼接的方式合成纹理,合成结果可表示为一系列切割路径的组合,仅需保存这些切割路径即可在渲染时实时重建出纹理图像.通过在预处理中计算得到一组误差小的平行切割路径,合成时无需进行匹配,使得合成速度大幅提高.该算法对于在水平和垂直方向具有自相似性的纹理具有较高的合成质量.     

基于显著结构元素的纹理合成

某些样本纹理中包含按一定的特征分布的显著结构元素,而现有像素级别纹理合成算法难以保持样本纹理中显著结构元素的完整性以及分布特征等人眼更高感知层次的信息.本文提出了一种基于显著结构元素的纹理合成算法.首先,提取样本纹理中显著结构元素,根据各元素的空间位置建立邻接关系,分析每个结构元素的邻域信息,把结构元素的分布建模为Markov随机场模型.在合成过程中,采用邻域匹配算法,在样本纹理中查找最合适的结构元素,并将其添加到目标纹理中.另外,本文在后处理中通过添加噪声对显著结构元素进行各种随机变换,增加了目标纹理的多样性,实验结果表明,对于半结构性纹理,本文合成结果符合更高层次人眼感知特征.     

Salient structural elements based texture synthesis

Salient structural elements are ubiquitous in natural textures, and their distribution exhibits some stochastic distribution features. Current texture synthesis algorithms can neither preserve the integrity of the elements nor capture this distributive information. We present an algorithm to treat this high-level visual information. Here, we address the issue by taking specific care of the structural elements. Our texture synthesis process grows the target texture one structural element at a time. A Markov ...     

基于Ashikhmin和Kong纹理合成算法的改进方法

Ashikhmin和Kong等人分别于2001年和2002年提出的纹理合成算法是当今典型的两种纹理合成算法,虽然前者对大部分自然纹理合成有不错的效果,但对变化较平缓的纹理合成效果不佳,而后者在合成时的时间复杂度较高.在上述两种算法的基础上,结合其优点,提出了一种把搜索范围限制在当前决的邻域的新的合成算法,并取得了理想的效果.     

Color texture analysis based on fractal descriptors

Color texture classification is an important step in image segmentation and recognition. The color information is especially important in textures of natural scenes, such as leaves surfaces, terrains models, etc. In this paper, we propose a novel approach based on the fractal dimension for color texture analysis. The proposed approach investigates the complexity in R, G and B color channels to characterize a texture sample. We also propose to study all channels in combination, taking into consideration the correlations between them. Both these approaches use the volumetric version of the Bouligand–Minkowski Fractal Dimension method. The results show a advantage of the proposed method over other color texture analysis methods.     

Font recognition based on global texture analysis

We describe a novel texture analysis-based approach toward font recognition. Existing methods are typically based on local typographical features that often require connected components analysis. In our method, we take the document as an image containing some specific textures and regard font recognition as texture identification. The method is content-independent and involves no detailed local feature analysis. Experiments are carried out by using 14000 samples of 24 frequently used Chinese fonts (six typefaces combined with four styles), as well as 32 frequently used English fonts (eight typefaces combined with four styles). An average recognition rate of 99.1 percent is achieved. Experimental results are also included on the robustness of the method against image degradation (e.g., pepper and salt noise) and on the comparison with existing methods     

Personal identification based on iris texture analysis

With an increasing emphasis on security, automated personal identification based on biometrics has been receiving extensive attention over the past decade. Iris recognition, as an emerging biometric recognition approach, is becoming a very active topic in both research and practical applications. In general, a typical iris recognition system includes iris imaging, iris liveness detection, and recognition. This paper focuses on the last issue and describes a new scheme for iris recognition from an image sequence. We first assess the quality of each image in the input sequence and select a clear iris image from such a sequence for subsequent recognition. A bank of spatial filters, whose kernels are suitable for iris recognition, is then used to capture local characteristics of the iris so as to produce discriminating texture features. Experimental results show that the proposed method has an encouraging performance. In particular, a comparative study of existing methods for iris recognition is conducted on an iris image database including 2,255 sequences from 213 subjects. Conclusions based on such a comparison using a nonparametric statistical method (the bootstrap) provide useful information for further research.     

Combining shape analysis and texture pattern for palmprint identification

Multimedia Tools and Applications - We propose an efficient method for principal line extraction from the palmprint and geometric framework for analyzing their shapes. This representation, along...     

改进的自然动态纹理综合算法

动态纹理综合技术是近年来计算机图形学领域研究的热点与难点之一.动态纹理综合技术在虚拟现实、电脑动画等领域有着广泛的应用.将Kernel PCA算法引入到动态纹理的分析与综合中,并与传统的基于线性PCA的动态纹理算法相比较.实验数据表明,基于Kernel PCA的改进算法在动态纹理描述和综合效果上均比线性PCA算法更好.     

Texture evolution: 3D texture synthesis from single 2D growable texture pattern

An efficient model-independent 3D texture synthesis algorithm based on texture growing and texture turbulence is presented to create vivid 3D solid texture from a single 2D growable texture pattern. Given a 2D texture pattern of some growable material, our technique is able to create an anisotropic 3D volumetric texture cube to simulate the evolution of the material in 3D. An effective tiling scheme is designed to save computation and storage costs. Target objects are directly dipped into the synthesized 3D texture volume to generate creative, sculpture-like models that can be visualized with interactive speed. Our method is conceptually intuitive, computationally fast, and storage efficient compared with other solid texturing methods. As opposed to conventional 2D texture mapping work on polygonal surfaces, our approach is capable of decorating 3D point-rendering systems seamlessly. Furthermore, our combination of texture turbulence and texture growing techniques provides an attractive way to synthesize and tile natural 2D texture patterns, or generate simple but interesting motion textures.     

Possibilities of texture based motion analysis

Analysis of motion patterns in the human locomotion apparatus is important in many clinical areas like orthopaedics, physiotherapy, neurology, and sports medicine. Today marker based human motion analysis (HMA) is completely dominant in the clinical context. Technically, these systems are stable and dependable, and about a dozen variants are commercially available. One drawback of such systems is the time consuming and error prone marker placement. The purpose of the present contribution is to show that it is possible, with existing simple technology and methods, to build systems that do not depend on anatomically placed markers and yet produce an accuracy in knee joint center estimation comparable to marker based systems. It is shown that texture based methods can give estimates of knee joint center of rotation that can be compared to knee joint center estimates from marker based systems. Due to different definitions of the knee joint center position some bias is seen between the two estimates.     

基于纹理分析的改进型Nagao滤波器

介绍了Nagao滤波器的基本原理,针对传统Nagao滤波器滤波后图像存在伪像以及用计算机实现处理速度慢等缺点,提出了一种基于纹理分析的改进型Nagao滤波器.通过对图像进行纹理分析,得到图像纹理复杂度指标,并用该指标作为Nagao滤波器选择模板的参数.实验分析表明,该方法可以很好地克服传统Nagao滤波器的不足,在进行图像自适应滤波时取得了比较好的效果,非常适合于对计算机处理速度要求比较高的应用.     

A clustering method based on multidimensional texture analysis

Considering the analogy between image segmentation and cluster analysis, the aim of this paper is to adapt statistical texture measures to describe the spatial distribution of multidimensional observations. The main idea is to consider the cluster cores as domains characterized by their specific textures in the data space. The distribution of the data points is first described as a multidimensional histogram defined on a multidimensional regular array of sampling points. In order to evaluate locally a multidimensional texture, a co-occurrence matrix is introduced, which characterizes the local distribution of the data points in the multidimensional data space. Several local texture features can be computed from this co-occurrence matrix, which accumulates spatial and statistical information on the data distribution in the neighborhoods of the sampling points. Texture features are selected according to their ability to discriminate different distributions of data points. The sampling points where the local underlying texture is evaluated are categorized into different texture classes. The points assigned to these classes tend to form connected components in the data space, which are considered as the cores of the clusters.     

Noise robust and rotation invariant texture classification based on local distribution transform

Multimedia Tools and Applications - Applying local binary pattern (LBP) to images with uniform distribution leads to generate discriminative features; however, the distribution of all images is not...     

基于新分布域和叠加纹理的飘雪模拟

针对传统的基于粒子系统的飘雪模拟中,粒子数量大、实时性差,且造成很多视线之外不可见粒子的资源浪费等不足,提出了一种基于新分布域和叠加纹理的飘雪模拟方法.在分布域的优化上,采用新的层次分布域来产生粒子,同时引入了叠加纹理的概念,并结合LOD技术,对不同LOD层次上的粒子采用不同的叠加纹理,最后在粒子消亡的判断条件上采用了局部判断的新算法.该方法在不影响真实感的情况下减少了计算量,有效提高了虚拟场景中飘雪模拟的逼真度和实时性.     

New local binary pattern approaches based on color channels in texture classification

Multimedia Tools and Applications - In this paper, four novel, simple and robust approaches, which are left to right local binary patterns (LBPLL2R), top to down local binary patterns (LBPT2D),...     

基于场向参数化的肌肉纤维纹理合成研究

虚拟手术系统研究是计算机图形学的一个重要领域,为了提高肌肉纤维纹理合成的真实感与实时性,文章采用了基于场向参数化的方法,并结合最光滑方向场进行了三维模型上的肌肉纤维纹理映射与合成,通过布置奇异点,模拟肌肉纤维损伤的状态。该系统实现了场向参数化的可视化及肌肉纤维纹理合成的简单交互,实验结果表明,系统的实时性与真实感均得到提高。     

在点模型上实现三维纹理合成的算法

为了避免网格重建过程而直接在三维点采样表面上进行纹理合成,研究了在点模型上的三维纹理合成的算法。利用KDtree这种数据结构在离散采样点上构建点与点的邻域关系,通过投影和建立匹配窗得到每一个待合成纹理的点与样图的映射关系,根据映射关系在样图中找出与待定点纹理值最佳匹配的点。最后将该匹配点的纹理值赋给待定点,同时结合邻域关系实现多点同时赋值。实验结果表明,该算法能有效地保持了生成的纹理结构和视觉效果的连续性和平滑性,具有耗时短、灵活可控、较好的鲁棒性等特点。