基于统计模型的书法创作模拟

人们对抽象思维与形象思维的认识极不平衡,对形象思维过程的研究尚属阙如.书法创作是典型的形象思维过程.文中给出基于带参数的统计模型(X=M(b))的书法笔划变形方法,通过调节参数可生成新风格的笔划.其过程包括从笔划轮廓获得训练点集、利用广义Procrustes分析法对齐、由主成分分析法得到特征等,并以隶书中典型的"一"划为例,讨论模拟创作结果.要实现人工智能,形象思维的模拟、模式和模型是逐步要考虑的问题.目前的工作只是第一步.     

Nonparametric Bayesian Image Segmentation

Image segmentation algorithms partition the set of pixels of an image into a specific number of different, spatially homogeneous groups. We propose a nonparametric Bayesian model for histogram clustering which automatically determines the number of segments when spatial smoothness constraints on the class assignments are enforced by a Markov Random Field. A Dirichlet process prior controls the level of resolution which corresponds to the number of clusters in data with a unique cluster structure. The resulting posterior is efficiently sampled by a variant of a conjugate-case sampling algorithm for Dirichlet process mixture models. Experimental results are provided for real-world gray value images, synthetic aperture radar images and magnetic resonance imaging data.     

一维统计量的椭圆检测法

数字影像中目标的识别是十分关键的,该文以椭圆作为研究对象,在对于基于二维随机变量的以HU不变矩为代表的不变矩算法上,提出了基于动差方法建立一维的随机统计量,并且证明该随机变量的三级动差和四级动差均为一常量。由于本算法只使用一维随机变量且该统计量又很容易获得,成为了其突现的优越性。     

改进的χ~2统计文本特征选择方法

特征选择是当今研究领域的一个热点,尤其是文本分类领域中的热点。针对χ2统计方法的两个缺陷:降低了低频词的权重和提高了很少在指定类中出现但普遍存在于其他类的特征在该类中的权重,对χ2统计方法进行改进,并通过做模拟和对比实验,对比改进前后的方法对文本分类的影响。在模拟和对比实验中,改进后方法的分类效果要好于传统的方法。     

鲁棒的高阶双边滤波去噪算法

提出了一种统一的局部高阶双边滤波算法.与传统的双边滤波去噪算法不同,该算法通过引入鲁棒统计理论获得模型表面较为准确的几何属性;进而在曲率空间中对包含主曲率和Frenet标架的表面几何属性进行各向异性的滤波,既有利于保持模型的细节,又能保证曲面的光滑性;与此同时,优化各个顶点的法向;最后在优化后的几何属性引导下,在几何空间中进行高阶双边滤波去噪.实验结果表明,即使在大噪声的情况下,该算法仍然能够有效地保持模型细节,避免模型的收缩和顶点漂移.     

中国图像工程：2008

该文是关于中国图像工程的年度文献综述系列之十四。为了使国内广大从事图像工程研究和图像技术应用的科技人员能够较全面地了解国内图像工程研究和发展的现状,并能够方便地查询有关文献,现从2008年在国内15种有关图像工程重要中文期刊的共120期上发表的3 359篇学术研究和技术应用文献中,选取出915篇属于图像工程领域的文献,并根据各文献的主要内容将其分别归入图像处理,图像分析,图像理解,技术应用和综述5个大类,然后进一步分入23个专业小类（与去年相同）。在此基础上还进行了各期刊各类文献的统计和分析。根据统计分析结果可看到,我国图像工程在2008年许多新进展的情况。特别值得指出的是,在上述15种期刊上所发表的图像工程文献数量在2008年继续增加并达到历史最高,显示了图像工程在中国继续蓬勃发展的趋势。     

Cognitive-Mathematical Approaches for Evaluating Architectural Contextual Fit

The main goal of this study is to apply a scientific quantitative approach to the investigation of contextual fit. This is approached mathematically within the framework of cognitive science and research on categorization and prototypes. Two experiments investigated two leading mathematical-cognitive approaches for explaining people’s judgment of contextual fit of a new building with an architectural/urban context: prototype approach and feature frequency approach. The basic concept is that people represent the built environment via architectural prototypes and/or frequencies of encountered architectural features. In the first experiment, a group of twelve participants performed rank order tasks on artificially created architectural patterns, for the purpose of psychological scaling. Perceptual distances among all patterns were mathematically determined. In the second experiment, three groups of architectural patterns were constructed to represent assumed architectural contexts. The prototype of each context was mathematically determined according to prototype cognitive model, and based on the distances calculated in the first experiment. Fifty-six students participated in the main experiment, in which they rank ordered a group of fifteen architectural patterns in terms of contextual fit to each of the three architectural contexts. Participants’ rank order data of the fifteen patterns were regressed on both the perceptual distances from prototypes, and numbers of features shared with each architectural context. Results indicated that both prototype and feature frequency approaches significantly accounted for important portions of participants’ judgments. However, participants tended to prefer one approach to the other according to context composition. Results have implications for both research on utilizing cognitive-mathematical models in architectural research and on urban design guidelines and control.     

Shopping System Model in Electronic Commerce

Despite its name, e-commerce is not fully automated. Typically, online transactions require a significant level of human intervention. Customers undertake the search for products, services, potential vendors and business partners. They evaluate alternatives, decide what goods to buy and when, from which vendor, and how much they are willing to pay for. They engage in potential negotiations, carry out the transactions and so on. As those markets become mature, new products and services, as well as new practi...     

学生体检数据统计及资料管理系统软件设计

学生健康体检是中小学必做的一项重要工作。长期以来,基层保健医生一直从事着繁重的手工报表统计工作,不但工作繁多,而且出错的几率很高,效率低。本文依据现行的学生体检标准以及多年工作实践,采用Delphi平台开发,目的在于把基层保健医生从繁重的手工劳动中解放出来,及时提供高效、准备的体检数据。因此,本文对于提高此项工作的工作效率,改进工作方法,具有参考意义。     

Blind omnidirectional image quality assessment with representative features and viewport oriented statistical features

With the development of information technologies, various types of streaming images are generated, such as videos, graphics, Virtual Reality (VR)/omnidirectional images (OIs), etc. Among them, the OIs usually have a broader view and a higher resolution, which provides human an immersive visual experience in a head-mounted display. However, the current image quality assessment works cannot achieve good performance without considering representative human visual features and visual viewing characteristics of OIs, which limited OIs’ further development. Motivated by the above problem, this work proposes a blind omnidirectional image quality assessment (BOIQA) model based on representative features and viewport oriented statistical features. Specifically, we apply the local binary pattern operator to encoder the cross-channel color information, and apply the weighted LBP to extract the structural features. Then the local natural scene statistics (NSS) features are extracted by using the viewport sampling to boost the performance. Finally, we apply support vector regression to predict the OIs’ quality score, and experimental results on CVIQD2018 and OIQA2018 Databases prove that the proposed model achieves better performance than state-of-the-art OIQA models.