一种针对有机分子的新式子结构匹配法——树状结构数据匹配

提出一种针对有机分子的新的子结构匹配方法 ,子结构采用树状结构数据表示 ,方法简单灵活 ,匹配快速准确。     

一种针对有机分子的新式子结构匹配法——树状结构数据匹配

提出一咱对有机分子的新的子结构匹配方法,子结构采用树据表示,方法简单灵活,匹配快速准确。     

快速构造植物几何结构的子结构算法

顺序地模拟符合植物学生物特征的复杂树结构会占用很多计算机资源。为减少对计算机资源的占用，提出了一种从最简单的子结构起，通过子结构的引用来形成复杂结构的方法。由于在该方法中重复出现的结构只被计算一次，因此不仅可以提高复杂结构的计算速度，而且可以降低几何信息的存储量。该几何信息不仅包括所模拟植物在各个生长周期的结构，而且包括了每个子结构的具体形态。尽管这是一种自上而下的算法，但由于子结构方法能够实现弯曲枝条的模拟，并能产生重复生长的结构和花序结构，因此具有通用性。     

计算机辅助分子模型系统－MMBS

计算机辅助分子模型系统ＭＭＢＳ采用两种输入方法，线型编码法和二维图形法，模型生成采用三维碎片子结构构造法，并采用快速子结构匹配实现结构感知。系统具有较强的图形显示和操作功能。     

计算机辅助分子模型系统—MMBS

计算机辅助分子模型ＭＭＢＳ采用两种输入方法，线型编码法和二维图形法，模型生成有杉三维碎片子结构构造法，并采用快速子结构匹配实现结构感知。系统具有较强的图形显示和操作功能。     

NKChemSQL——针对MySQL的化学信息学扩展

化学数据库是进行化学信息学研究的重要资源,分子属性与指纹计算、分子结构格式转换、分子相似度匹配、精确匹配和子结构匹配以及分子结构图片导出等,都是必需的基本服务内容。应用广泛的数据库系统MySQL却缺乏这些功能,难以满足化学信息处理、网站开发等开发的需求。NKChemSQL是自行编制的MySQL扩展库,通过对开源软件OpenBabel的功能进行包装,以SQL语言的格式完成相应操作。NKChemSQL具有良好的运行表现,经过对含26万余条分子结构信息的NCI数据库进行的测试,全结构匹配只需不到1秒而子结构匹配达300个结构/秒,相似度匹配则达1万个结构/秒。NKChemSQL为开发化学信息学软件和网站提供了非常便利的新方式。     

用边缘金字塔结构实现Hausdorff距离匹配

为了快速准确地在海量图像中搜索模板的所有实例，提出运用边缘金字塔结构来实现Hausdorff距离匹配．根据模板的边缘自适应地确定边缘金字塔分解次数和抽取模式，然后通过金字塔结构的引导搜索策略实现快速匹配．对以水平和垂直边缘为主的集成电路显微图像，文中算法体现出优越的匹配性能．在集成电路显微图像和一般图像上分别测试的实验结果表明：文中算法在获得良好的匹配效果的同时，大幅减少了匹配时间．     

基于框架的虚拟装配运动引导

为了在交互式装配过程中精确地定位零件模型,提出一种基于框架的装配运动引导方法.该方法将典型装配过程性知识封装到过程框架中,将蕴藏在零件模型B-rep中的工程信息封装到特征框架中,与场景匹配引擎一起构成框架系统;框架系统采用场景匹配的方式来捕获操作者的装配意图(即匹配成功的过程框架),由匹配成功的过程框架来引导装配运动,并由过程框架中规定的动作和时机来完成装配件的精确定位.应用实例结果表明,文中方法有效地克服了操作者通过交互设备对装配零件运动控制的不精确性问题.     

工程化学数据库中分子结构信息的处理

工程化学数据库(ECDB)中,分子结构信息的存储、子结构检索和图形显示查询结果是实现结构数据库功能的基础.本文就研究这三问题,在数据存储方面设计了按MOL文件结构的特殊存储方法,压缩大量存储;在子结构检索方面,改进VF2算法的效率;开发图形显示模块,设计子结构检索平台.     

面向实时事件流的复杂事件处理方法

复杂事件处理是一种动态环境下对事件流进行分析的技术。复杂事件处理技术通常基于有限状态自动机实现,匹配过程中会在事件流上产生大量且重叠的部分匹配,有限状态自动机需维护大量的重复匹配状态,导致基于该技术的方法都会出现冗余计算的问题。为了提高复杂事件处理的匹配效率,提出了使用复杂事件实例覆盖技术来实现复杂事件处理的方法。通过设计临时匹配链式分区存储结构以及基于此结构的匹配算法,来利用复杂事件实例覆盖减少冗余计算,从而实现匹配效率的提升。在模拟数据集和真实数据集上进行了实验测试与分析,与两种常用的复杂事件处理技术进行比较。实验表明,提出方法能够在保证匹配正确性的同时有效地减少匹配过程中的冗余计算,提高整体匹配效率。     

On-line recognition of handprinted Kanji characters

Difficulties in Kanji (Chinese character) recognition stem from its large character set (about 5000 characters) and the large number of strokes (up to about sixty) in each character.

The paper describes a preliminary approach to this Kanji recognition problem. In the present method, a handprinted Kanji character is coded into a symbol string using the binary relation between stroke and reference zone. Two symbol string recognition methods are proposed and investigated; the direct matching recognition (DMR) method and the unit structure recognition (USR) method.

The DMR method worked efficiently for characters which have up to five strokes. The USR method represents Kanji characters with a structural unit combination. This method worked efficiently for multi-stroke characters and greatly reduced dictionary update labor.     

一种笔段序列匹配联机汉字识别方法

文中针对行书体汉字的识别,提出一种笔段序列匹配汉字识别方法。选择笔段数、笔段书写顺序、笔段位置作为主要的识别特征。首先,在预处理阶段,为了减小汉字类内分散性,采用笔段密度均衡化非线性规整法对笔段位置进行了非线性规整;进而在笔段序列的基础上,采用动态规划算法寻找待识笔段序列与候选笔段序列的最优匹配路径;根据此路径,得到匹配笔段集,缺少笔段和多余笔段;然后计算出待识字与每个候选字的识别距离;最后,对识     

Cascade Markov random fields for stroke extraction of Chinese characters

Extracting perceptually meaningful strokes plays an essential role in modeling structures of handwritten Chinese characters for accurate character recognition. This paper proposes a cascade Markov random field (MRF) model that combines both bottom-up (BU) and top-down (TD) processes for stroke extraction. In the low-level stroke segmentation process, we use a BU MRF model with smoothness prior to segment the character skeleton into directional substrokes based on self-organization of pixel-based directional features. In the high-level stroke extraction process, the segmented substrokes are sent to a TD MRF-based character model that, in turn, feeds back to guide the merging of corresponding substrokes to produce reliable candidate strokes for character recognition. The merit of the cascade MRF model is due to its ability to encode the local statistical dependencies of neighboring stroke components as well as prior knowledge of Chinese character structures. Encouraging stroke extraction and character recognition results confirm the effectiveness of our method, which integrates both BU/TD vision processing streams within the unified MRF framework.     

一种有效的并行汉字／字符串相似检索技术

本文提出了一种有效的并行汉字／字符串相似检索技术．通过引入搜索状态向量及字符一模式匹配向量，该技术将字符串匹配比较转化为简单的整数字位运算，通过对字符串方向相反的搜索有效地实现了多处理机对汉字／字符串的并行相似检索．文中也给出了并行实现算法，同时分析了算法的复杂性．     

Model-based stroke extraction and matching for handwritten Chinese character recognition

This paper proposes a model-based structural matching method for handwritten Chinese character recognition (HCCR). This method is able to obtain reliable stroke correspondence and enable structural interpretation. In the model base, the reference character of each category is described in an attributed relational graph (ARG). The input character is described with feature points and line segments. The strokes and inter-stroke relations of input character are not determined until being matched with a reference character. The structural matching is accomplished in two stages: candidate stroke extraction and consistent matching. All candidate input strokes to match the reference strokes are extracted by line following and then the consistent matching is achieved by heuristic search. Some structural post-processing operations are applied to improve the stroke correspondence. Recognition experiments were implemented on an image database collected in KAIST, and promising results have been achieved.     

运动串:一种用于行为分割的运动捕获数据表示方法

运动数据的行为分割是运动捕获过程中非常重要的一环.针对现有分割方法的不足,提出了一种可用于行为分割的运动数据表示方法,并基于该表示实现了数据的行为分割.运动数据经过谱聚类(spectral clustering)、时序恢复和最大值滤波法(max filtering)后生成一个字符串,该字符串称为运动串,然后采用后缀树(suffix tree)分析运动串,提取出所有静态子串和周期子串,对这些子串进行行为标注,从而实现运动数据的行为分割.实验表明,基于运动串的分割具有较好的鲁棒性和分割效果.     

On-line handwritten Chinese character recognition via a fuzzy attribute representation

Chinese characters are constructed by strokes according to structural rules. Therefore, the geometric configurations of characters are important features for character recognition. In handwritten characters, stroke shapes and their spatial relations may vary to some extent. The attribute value of a structural identification is then a fuzzy quantity rather than a binary quantity. Recognizing these facts, we propose a fuzzy attribute representation (FAR) to describe the structural features of handwritten Chinese characters for an on-line Chinese character recognition (OLCCR) system. With a FAR. a fuzzy attribute graph for each handwritten character is created, and the character recognition process is thus transformed into a simple graph matching problem. This character representation and our proposed recognition method allow us to relax the constraints on stroke order and stroke connection. The graph model provides a generalized character representation that can easily incorporate newly added characters into an OLCCR system with an automatic learning capability. The fuzzy representation can describe the degree of structural deformation in handwritten characters. The character matching algorithm is designed to tolerate structural deformations to some extent. Therefore, even input characters with deformations can be recognized correctly once the reference dictionary of the recognition system has been trained using a few representative learning samples. Experimental results are provided to show the effectiveness of the proposed method.     

允许错误的（汉字）字符串快速检索技术

在计算机应用的诸多领域中都会遇到字符串似检索问题。本提出了一种技术。它通过应用搜索状态向量及字符－模式匹配向量，将字符串匹配比较转化简单的整数字位运算，有效地解决了字符／汉字串的相似匹配问题，中也给出了实现算法并分析了算法的复杂性。     

最大类间方差车牌字符分割的模板匹配算法

提出一种基于模板匹配的最大类间方差车牌字符分割算法。根据字符串的结构和尺寸特征，设计了车牌字符串模板，该模板在车牌区域滑动匹配进行分类，并结合最大类间方差判决准则，确定最佳匹配位置，分割车牌字符。实验表明，该方法自适应性强，可以获得最优的分割效果。