Automatic generation of artistic chinese calligraphy

Chinese calligraphy is among the finest and most important of all Chinese art forms and an inseparable part of Chinese history. Its delicate aesthetic effects are generally considered to be unique among all calligraphic arts. Its subtle power is integral to traditional Chinese painting. A novel intelligent system uses a constraint-based analogous-reasoning process to automatically generate original Chinese calligraphy that meets visually aesthetic requirements. We propose an intelligent system that can automatically create novel, aesthetically appealing Chinese calligraphy from a few training examples of existing calligraphic styles. To demonstrate the proposed methodology's feasibility, we have implemented a prototype system that automatically generates new Chinese calligraphic art from a small training set.     

三维虚拟环境中的书法创作

为了充分利用数字化技术促进书法艺术的教学和发展,提出并实现了虚拟化书法创作系统.首先构建基于三角网格的毛笔虚拟模型;然后通过常用曲线拟合笔画书写路径,并在笔画路径上指定关键帧,以表现书写时毛笔在相应位置上的节奏快慢和提、按、顿、挫等状态;最后实时绘制书法作品并渲染书写过程.用户可以随意用文中系统进行书法创作,在三维环境中逼真地展示书法创作的全过程.实验结果表明,所构建的毛笔虚拟模型计算量小、实时性强,创作效果与真实毛笔的书写效果非常接近.     

基于毛笔建模的机器人书法系统

针对机器人书法系统存在仅考虑毛笔笔直状态下机器人书写的问题,提出了一种新的机器人书法系统,可使机器人能够在倾斜状态下书写汉字。该系统首先分析毛笔足迹,建立一种适合用于机器人毛笔书写的基于线性回归算法的笔触模型;然后使用遗传算法从笔画图像获得轨迹信息,加入了起笔、行笔、收笔规则,生成虚拟笔画图像;最后采用B样条算法实现机器人路径规划,坐标变换完成姿态计算,从而进行实际书写。机器人书法系统提取了3种笔画特征作为评价指标,实验结果表明:机器人毛笔书法系统可以得到较好的书写效果。     

一个联机书法临摹系统的设计与实现

提出一个联机书法临摹系统,对传统的中国书法学习过程进行计算机模拟.系统基于Wintab标准捕获书写实时信息,并以一维基元序列模型表示和存储书法范字;学习者在线临摹时,系统基于椭圆模型和动态信息进行书法范字绘制,模拟范字创作时的书写笔顺、运笔方法、提按轻重、行笔节奏等体现书法美学内涵的动态过程,再现结果如同老师身临示范.系统可作为中国书法教育辅助软件或自学工具.     

基于经验的虚拟毛笔模型

书法艺术的计算机模拟吸引了越来越多的研究．为了达到中国书法艺术的实时仿真，给出了一种基于经验的虚拟毛笔模型．该模型着眼于实际书法的经验，可以克服基于粒子系统的虚拟毛笔的表达力匮乏和基于实体物理模型的虚拟毛笔的参数调整复杂性，并且避免了传统模型计算复杂的缺点．通过利用实际书法和国画过程的实验经验，虚拟毛笔可以高效地实时操作，并实现枯笔、飞白与渗透，得到可与真实毛笔笔迹媲美的效果．     

A virtual 3D interactive painting method for Chinese calligraphy and painting based on real-time force feedback technology

A novel 3D interactive painting method for Chinese calligraphy and painting based on force feedback technology is proposed. The relationship between the force exerted on the brush and the resulting brush deformation is analyzed and a spring-mass model is used to build a model of the 3D Chinese brush. The 2D brush footprint between the brush and the plane of the paper or object is calculated according to the deformation of the 3D brush when force is exerted on the 3D brush. Then the 3D brush footprint is obtained by projecting the 2D brush footprint onto the surface of the 3D object in real time, and a complete 3D brushstroke is obtained by superimposing 3D brush footprints along the painting direction. The proposed method has been successfully applied in a virtual 3D interactive drawing system based on force feedback technology. In this system, users can paint 3D brushstrokes in real time with a Phantom Desktop haptic device, which can effectively serve as a virtual reality interface to the simulated painting environment for users.     

Trajectory generation of the writing–brush for a robot arm to inherit block–style Chinese character calligraphy techniques

This paper relates the trajectory generation of the writing-brush for a robot arm to inherit Chinese character calligraphy (CCC) techniques. First, to preserve the characters written by famous calligraphers in Chinese history, we constructed a CCC database which contains 29 456 characters written by different calligraphers in different styles (ancient, angular, block, semi-cursive and cursive style). With this CCC database, it is possible to search, restore and append the calligraphy writing for a specific character. Second, we mainly relate the inheritance of CCC. Because CCC is not a static thing, but a dynamic process of an activity which concerns a lot of complicated factors such as the pressure and speed control of the writing brush, how to write the start and end of strokes, etc., we propose to inherit this dynamic process by a robot. This paper is limited to discussing how to inherit the writing techniques for block-style calligraphy writing by a robot arm. The total number of Chinese characters is more than 800 000. These characters can be constructed by basic strokes. There are 28 different kinds of strokes used to construct all of these characters. The skeleton of a stroke is decided by the control points that exist within the stroke. The shape of a stroke is determined by the trajectory derived from the control points and the pressure to the writing brush. The control points for 28 strokes are given and the control techniques for a robot to write these strokes in block style are developed. At present, the robot can write any character in block style.     

Droplet: A virtual brush model to simulate Chinese calligraphy and painting

This paper proposes a virtual brush model based on droplet operation to simulate Chinese calligraphy and traditional Chinese painting in real time. Two ways of applying droplet model to virtual calligraphy and painting are discussed in detail The second droplet model is more elaborated and can produce more vivid results while being slightly more time-consuming. The novel feature of the proposed droplet virtual brush model successfully enables the simulation painting system to overcome the poor expressional ability of virtual brush based on particle system and avoids the complex evaluation of physical brush with solid model. The model, derived from the actual calligraphy and painting experience, due to the simplicity of the droplet operation and its powerful expressive ability, considerably improves the performance of the simulation system and maintains painting effect comparable with real brush by supporting special Chinese brush effect such as dry brush, feng and stroke diffusion.     

基于审美特征的书法评价模型构造与实现

传统的书法学习,需要教师要对学生习作进行分析和点评,一旦离开教师的指导,提高就变得十分困难.基于此,提出一个基于审美特征的书法评价模型,实现对传统书法教学过程的计算机模拟.借助该系统,教师可以录入书法范字;学生可以运用手写设备进行在线临摹练习.练习结束后,系统能够给出学生习作在结构与笔法两方面详细的指导意见.实验表明,模型为书法学习提供了有效帮助.     

Hierarchical Approximate Matching for Retrieval of Chinese Historical Calligraphy Character

As historical Chinese calligraphy works are being digitized, the problem of retrieval becomes a new challenge. But, currently no OCR technique can convert calligraphy character images into text, nor can the existing Handwriting Character Recognition approach does not work for it. This paper proposes a novel approach to efficiently retrieving Chinese calligraphy characters on the basis of similarity： calligraphy character image is represented by a collection of discriminative features, and high retrieval speed with reasonable effectiveness is achieved. First, calligraphy characters that have no possibility similar to the query are filtered out step by step by comparing the character complexity, stroke density and stroke protrusion. Then, similar calligraphy characters axe retrieved and ranked according to their matching cost produced by approximate shape match. In order to speed up the retrieval, we employed high dimensional data structure - PK-tree. Finally, the efficiency of the algorithm is demonstrated by a preliminary experiment with 3012 calligraphy character images.     

Research on personalized recommendation hybrid algorithm for interactive experience equipment

Interactive calligraphy experience equipment has the characteristics of a large amount of data, various types, and strong homogeneity, which makes it difficult for users to find interesting resources. In this article, a hybrid personalized recommendation algorithm is proposed, which uses collaborative filtering and content-based recommendation methods in turn to make recommendations. In the initial recommendation, Latent Dirichlet Allocation (LDA) topic model is used to reduce the dimension of high-dimensional user behavior data and establish a user-writing theme matrix to reduce inaccurate recommendation caused by high sparsity data in collaborative filtering algorithm. The user interest list is obtained by calculating the similarity between users. Then, on the basis of the preliminary recommendation results, VGG16 model is used to extract the feature vector of the calligraphy image and calculate the similarity between the user's calligraphy words and the primary recommended calligraphy words, thus obtaining the final recommendation results. The experimental results verify the effectiveness and accuracy of the recommendation algorithm, which are better than other recommendation algorithms on the whole, and have important engineering guiding significance.     

论当代艺术视角下陶瓷书法对传统书法的借鉴与革新

传统书法与陶瓷书法都是中国传统艺术中的重要门类,融合了我国民族文化的独特内涵和精神面貌。纵观中国美术发展史,陶瓷书法始终没有完全脱离传统书法的影响和渗透,文章分别就其审美、气韵、意趣等角度谈陶瓷书法艺术与传统书法艺术的关联,旨在探索如何在当代艺术视角下创作出无愧于时代的艺术精品。     

基于结构约束生成对抗网络的书法汉字生成

目前书法汉字的生成研究在汉字生成过程中需要大量先验汉字组成信息,不仅对前期数据收集工作的要求较高,而且影响研究成果的扩展性.针对此问题,文中提出基于结构约束的条件堆叠生成对抗网络的书法汉字生成方法.将源汉字图像直接提取的汉字笔迹作为结构约束条件,通过条件堆叠生成对抗网络模型生成高质量的书法汉字.同时提出通过伪目标样本的...     

传统与现代的对话:书法在艺术设计中的应用

目前国内的艺术设计作品越来越脱离民族文化性和精神性。面对这种状况,借鉴传统艺术式样是解决这个问题的可行方法之一。在中国传统艺术中,书法具有其他艺术式样所没有的抽象性,在现代艺术设计中发挥着重要的作用。本文在探讨书法艺术特征和审美取向的同时,就书法在现代艺术设计中的表现形式,传统书法与现代艺术设计的关系进行探讨。并对今后艺术设计中书法元素的利用进行探析。     

Discovering calligraphy style relationships by Supervised Learning Weighted Random Walk Model

Chinese calligraphy is an important part of Chinese traditional culture. More and more calligraphy works are digitized, preserved and exhibited in digital libraries. Users may want to appreciate the style-similar works simultaneously. However, currently available services such as metadata-based browsing and searching can not satisfy such kind of requirement. To allow users to appreciate the style-similar works conveniently, we propose a Supervised Learning Weighted Random Walk Model to discover calligraphy style relationships. In the model, we consider the heterogeneity of both edges and nodes, and then use some preference pairs to learn the weights of different types of edges in the graph. After the weight learning, the style relationships can be discovered by random walk on the heterogeneous graphs. In order to solve the out-of-graph node problem, we pre-compute the personalized vector for each character or visual word, then utilize the Linearity Theory for vector addition to approximate the relationships between the new node and other nodes in graph. Then we demonstrate several applications which prove the effectiveness and efficiency of our proposed model and a user study for benefit verification. Finally, we explore some strategies to enhance the performance with the explicit or implicit user interaction including feedback, clickthrough data tracking.     

一种自动提取中国书画作品中印章图像的方法

在分析了中国书画印章图像特点的基础上,针对基于内容的书画作品图像检索领域中存在的"语义鸿沟"问题,提出了一种自动提取中国书画作品中印章图像的方法,并设计实现了该算法.通过对提取效果进行分析,证明该方法有较高提取率,这对书画作品中图像语义和特定图像鉴别的研究有重要意义.     

论包装设计中的书法魅力

书法艺术是最具有中国特色的艺术形式,也是一种抽象的符号艺术,在现代艺术设计中发挥着重要的作用。本文就中国汉字及书法进行了简要的阐述,对书法元素在包装设计中的表现形式、作用,以及书法艺术与包装设计的关系进行了论述。     

SentiVerb system: classification of social media text using sentiment analysis

This article proposes novel frameworks of SentiVerb and Spell Checker system, which extracts the reaction, mood, and opinion of users from social media text (SMT). The opinion of users is extracted from their written text on social media such as comments, tweets, blogs, feedbacks etc. and are classified as positive or negative opinion based on sentiment score of SMT using dictionary-based approach and a binary classifier. The dictionary-based approach uses opinion verb dictionary (OVD) to extract the sentiment of opinion verbs present in SMT. This OVD contain only opinion verbs along with their sentiment score. The various steps of the framework such as lower-case conversion, tokenization, spell checker, Part-of-Speech tagging, stop word elimination, stemming, sentiment score calculation, and classification of SMT has been discussed. A new concept of threshold negative parameter is first time introduced in this article. In the experiment, the proposed SentiVerb system’s performance is evaluated on three datasets such as Facebook comments on goods and services tax (GST) implementation in India, tweets on the debate between former president of USA Mr. Barack Obama and Mr. John McCain, and the movie reviews. Consequently, the implementation of the proposed SentiVerb system using rule-based classifier (RBC) gives the best performance result in term of accuracy with 82.5% on GST comments and 79.18% on Obama-McCain debate, which is better than the existing algorithms on the social issues related domain dataset(s). Also, system performance (accuracy of 71.3%) is better than others results on standard movie dataset.

     

基于深度学习的手写书法字体识别算法

为解决因手写书法作品种类繁多而识别困难的问题,降低人们观赏书法的门槛,本文提出了基于深度学习的手写书法字体识别算法.识别过程中首先使用投影法等图像处理方法对书法作品图像中的汉字进行定位和分割,然后分别利用GoogLeNet Inception-v3模型和ResNet-50残差网络进行书体风格识别和字形识别.实验结果表明...