基于纹样的计算机剪纸系统

以手工剪纸为对象，分析其造型，分解出构成剪纸的纹样，用计算机方法构成这些纹样库。用户创作时可在纹样库中选择所需纹样嵌入在指定位置上，实现对称性设计，系统能自动判断纹样是否相交，同时可灵活地更换纹样，生成不同的剪纸形象。该系统可以广泛地应用在装饰图案设计、电子贺卡、广告以及游戏、动画等领域。     

基于装饰纹样的剪纸图案设计方法

以传统剪纸图案为研究对象,分解出构成剪纸图案的纹样,将这些纹样分为独立纹样和复合纹样。通过对二维图形进行布尔运算等方法构建丰富的独立纹样库。以独立纹样为基础,应用扩大对称、渐变等图案设计技术建立复合纹样库,同时,对折叠剪纸效果进行模拟。实验结果表明,该方法能够根据需要生成不同形式的折叠剪纸图案。     

京剧脸谱剪纸合成方法

针对手工剪纸作品制作周期长、难以修改的问题,提出一种模拟真实剪纸效果的京剧脸谱合成方法。在分析传统京剧脸谱剪纸结构的基础上,构造五官、装饰和轮廓纹样。在京剧脸谱剪纸的创作过程中用户从纹样库中选取所需纹样,经调节纹样尺寸和分布后,将设计的脸谱形象与运用Ashikhmin自然纹理合成算法生成的剪纸纹理相融合。实验结果表明,该方法能够较好地模拟手工京剧脸谱剪纸的镂空效果,提升工作效率,便于设计人员在创作过程中更换纹样和修改作品,适用于室内装饰、广告设计和剪纸作品展示领域。     

基于遗传算法的剪纸图案创新设计

通过对剪纸造型的分析和概括,抽象出所需的纹样,利用遗传算法来生成纹样,并且在适应度函数的构建方面,增加了对曲线均匀度和平滑度的度量,以此构造丰富多彩的纹样库。然后通过对剪纸造型结构上的分析,对纹样库中的各种纹样进行自动选取及组装,产生各种各样风格不同的剪纸图案造型,并可根据实际需要进行人工修改。实验证明,该方法能够增强剪纸图案设计的创新性。     

基于小波变换和奇异值分解的剪纸纹样识别

针对民间传统剪纸艺术的计算机创作问题,在分析剪纸艺术特点的基础上,提出一种基于小波变换和奇异值分解的剪纸纹样识别方法.首先对剪纸纹样图像进行归一化和二值化处理,然后应用小波变换提取剪纸纹样图像的低频分量并进行奇异值分解,最后通过对奇异值进行归一化和降维处理作为最终的特征向量,利用最近邻分类器进行模式识别.实验结果表明,该方法能够有效地去除噪声干扰,较好的识别有一定艺术夸张变形的剪纸纹样.     

创意剪影拍摄

正剪影本来是剪纸形式的一种,是一门手工艺术。剪纸艺人用剪刀将黑色纸张(或者色彩较重的纸)剪成人、动物或其他物体的外在轮廓。应用在摄影中,主要是通过明亮的背景来衬托较暗的主体,不显示被摄主体的内部细节,完全靠外在轮廓的造型来塑造形象。下面首先简单介绍一下剪影拍摄的技巧,然后再通过一些优秀的剪影作品,来盘点一些创意思路。     

基于多分辨Fourier-Mellin变换的剪纸纹样识别算法

提出一种基于多分辨Fourier-Mellin的剪纸纹样识别算法。该算法先对剪纸纹样图像进行Fourier-Mellin变换,再对变换后的图像通过小波变换计算出各层方差和均值,得到剪纸纹样不同子带的特征值,应用支持向量机对剪纸纹样进行识别。实验证明,该方法不仅具有平移、旋转和尺度不变性,而且适用于有夸张艺术变形的剪纸纹样识别。     

应用R变换和奇异值分解的剪纸纹样识别

首先对剪纸纹样进行R变换,求出峰值数,对R变换数据进行归一化处理,通过奇异值分解得到图像识别的特征向量,根据特征向量值和峰值数对剪纸纹样的识别。使用该方法提取到的特征向量具有平移、旋转和尺度不变性,能较好地识别有一定艺术夸张变形的剪纸纹样。     

剪纸图案的构造模式分析和数字化建模

为了更好地对剪纸图案进行编辑、重用和个性化设计,提出一种剪纸图案的构造模式分析和数字化建模方法.首先对剪纸图像进行矢量化,获得各个独立形状的剪纸图案;然后采用改进的形状上下文方法对它们进行相似性聚类;最后检测和识别相似图案的空间分布模式,将输入剪纸图像转化为一个由元素层、相似层、纹样层、根结点组成的树状层次结构.文中提出的建模方法凸显了剪纸图案重复有序和模式化的构造特点,能够支持快速的几何连通性判断.实验结果表明,该方法能够大大降低个性化剪纸设计的难度,提高剪纸图案的编辑效率.     

基于不变矩和BP神经网络的剪纸纹样识别

针对剪纸纹样艺术夸张变形的特点,将剪纸图像进行预处理,提取7个不变矩作为剪纸纹样的特征向量,采用LM算法优化BP神经网络,通过归一化后的不变矩对BP神经网络进行训练,应用训练后的神经网络作为分类器对剪纸纹样进行模式识别,实验证明该方法能够较好地识别有一定艺术变形的剪纸纹样。     

面向三维剪纸的网格模型切割方法

提出了一种改进的三维网格模型切割算法,在切割每个图案时首先检查面片区域是否已被其他图案修改,并在修改之后对应的面片区域上进行切割且记录切割结果,最后将三维网格模型表面封闭剪纸图案内的顶点和面片剔除,得到像手工剪纸那样的镂空效果.三维剪纸可以广泛应用于动画、教育以及娱乐产业中.     

Matrix-pattern-oriented Ho-Kashyap classifier with regularization learning

Existing classifier designs generally base on vector pattern, hence, when a non-vector pattern such as a face image as the input to the classifier, it has to be first concatenated to a vector. In this paper, we, instead, explore using a set of given matrix patterns to design a classifier. For this, first we represent a pattern in matrix form and recast existing vector-based classifiers to their corresponding matrixized versions and then optimize their parameters. Concretely, considering its similar principle to the support vector machines of maximizing the separation margin and superior generalization performance, the modified HK algorithm (MHKS) is chosen and then a matrix-based MHKS classifier (MatMHKS) is developed. Experimental results on ORL, Letters and UCI data sets show that MatMHKS is more powerful in generalization than MHKS. This paper focuses on: (1) purely exploring the classification performance discrepancy between matrix- and vector-pattern representations; more importantly, (2) developing a new classifier design directly for matrix pattern.     

Image normalization for pattern recognition

In general, there are four basic forms of distortion in the recognition of planar patterns: translation, rotation, scaling and skew. In this paper, a normalization algorithm has been developed which transforms pattern into its normal form such that it is invariant to translation, rotation, scaling and skew. After normalization, the recognition can be performed by a simple matching method. In the algorithm, we first compute the covariance matrix of a given pattern. Then we rotate the pattern according to the eigenvectors of the covariance matrix, and scale the pattern along the two eigenvectors according to the eigenvalues to bring the pattern to its most compact form. After the process, the pattern is invariant to translation, scaling and skew. Only the rotation problem remains unsolved. By applying the tensor theory, we find a rotation angle which can make the pattern invariant to rotation. Thus, the resulting pattern is invariant to translation, rotation, scaling and skew. The planar image used in this algorithm may be curved, shaped, a grey-level image or a coloured image, so its applications are wide, including recognition problems about curve, shape, grey-level and coloured patterns. The technique suggested in this paper is easy, does not need much computation, and can serve as a pre-processing step in computer vision applications.     

Dynamic pattern denoising method using multi-basin system with kernels

In this paper, we propose a novel pattern denoising method that utilizes the topological property of a support that describes the distribution of normal patterns to denoise noisy patterns. The method first trains a support function which captures the domain of normal patterns and then construct a so-called multi-basin system associated with the trained support function. By moving noisy patterns along the trajectories of the multi-basin system, noise is removed while the pattern recovers its normality. The denoised pattern is obtained when the noisy pattern arrives at the attracting manifold generated by a set of normal patterns and this is the most similar normal pattern with the noisy pattern in the topological sense. Through simulations on some toy dataset and real image datasets, we show that the proposed framework effectively removes the noise while preserving the information contained in the noisy pattern.     

敦煌图案设计艺术的世俗性

作为象征性的表现艺术,敦煌图案设计艺术以抽象的形式,富有表现力的效果,传达了特定的观念。这些观念不仅有作为佛教艺术的宗教性因素,更多的则是表现人们日常生活的世俗性内容。敦煌石窟艺术中的装饰图案设计艺术,在抽象艺术形式的演变上,蕴含着由表现神到表现人,以及表现人神共处的世俗性和宗教性相结合的观念内涵。本文通过对敦煌图案设计艺术表达形式的探究,分析敦煌装饰图案设计艺术中蕴含的世俗性特征。