Exoskeleton: Curve network abstraction for 3D shapes

In this paper, we introduce the concept of an exoskeleton as a new abstraction of arbitrary shapes that succinctly conveys both the perceptual and the geometric structure of a 3D model. We extract exoskeletons via a principled framework that combines segmentation and shape approximation. Our method starts from a segmentation of the shape into perceptually relevant parts and then constructs the exoskeleton using a novel extension of the Variational Shape Approximation method. Benefits of the exoskeleton abstraction to graphics applications such as simplification and chartification are presented.     

Holistic recognition of handwritten character pairs

Researchers have thus far focused on the recognition of alpha and numeric characters in isolation as well as in context. In this paper we introduce a new genre of problems where the input pattern is taken to be a pair of characters. This adds to the complexity of the classification task. The 10 class digit recognition problem is now transformed into a 100 class problem where the classes are {00,…, 99}. Similarly, the alpha character recognition problem is transformed to a 26×26 class problem, where the classes are {AA,…, ZZ}. If lower-case characters are also considered the number of classes increases further. The justification for adding to the complexity of the classification task is described in this paper. There are many applications where the pairs of characters occur naturally as an indivisible unit. Therefore, an approach which recognizes pairs of characters, whether or not they are separable, can lead to superior results. In fact, the holistic method described in this paper outperforms the traditional approaches that are based on segmentation. The correct recognition rate on a set of US state abbreviations and digit pairs, touching in various ways, is above 86%.     

图象和视频的检索技术

随着网络技术的发展,多媒体数据将成为网络服务的主要内容,因此对多媒体数据管理问题的研究成为近几年的热点。由于媒体信息表现性质的不同,传统关系数据库的检索方式不再适用于图象和视频,因此,必须采用基于自身内容的检索方式。文章对基于内容的图象和视频检索技术分不同层次进行了全面的总结,内容包括依据基本特征,色彩、纹理、形状、和位置关系的技术,视频的场景分割、关键帧提取技术以及基于声音、文字的检索技术等,并阐述了各种方法的优缺点,现状及发展方向。     

鲁棒的多体印刷英文识别系统的实现

文章讨论了设计一个实用的多体英文识别系统中解决的主要问题。该系统能识别多达260种字体,包括斜体和黑体等字体,对训练集的识别率达到99%,对实际文本测试的错误率比TH-OCR2000低56%。文章详细阐述了文本行字切分,特征提取和分类器设计,以及后处理所使用的常用技术,对各种技术的特点进行了分析和比较,并提出了一些新的技术。文章对于OCR系统的设计具有一定的指导意义。     

Delphi应用程序与Microsoft Office的集成

本文论述Ｄelphi应用程序与Ｍicorsoft Office集成的原理并结合具体实例介绍几种Ｄelphi应用程序与Micorsoft Office集成的方法,重点介绍如何将Delphi的数据集ＤＡＴＡＳＥＴ的数据传送至Word文档或ＥＸＣＥＬ工作簿,形成新的工作表。     

MPEG-4视频标准及其在可视电话中的应用

本文主要介绍了ＭＰＥＧ－４的视频标准和算法,并应用于可视电话,实现了ＭＰＥＧ－４的编解码,将ＭＰＥＧ－４的性能与Ｈ．２６３进行了多方面测试,对于图象分割问题,使用了矩形形状和差值形状,经过测试,有一定使用价值。     

超长指令字技术

指令系统是决定计算机体系结构特征的最核心因素,本文首先对近几年发展起来的超长指令字技术的基本原理进行了科短的介绍,进而Ｉｎｔｅｌ公司研制的ＩＡ－６４超长指令字计算机的设计描述了超长指令字计算机的性能特点,最后简述ＶＬＩＷ技术对计算机技术结构发展的影响及其最近发展概况。     

铁道钢轨断面的计算机图象处理与仿真

利用计算机图象处理和仿真技术,对铁道钢轨断面进行快速检测与处理的研究。     

对粘连和缺损数字串分割的研究

把缺损和粘连的字符串分割成单个字符以便后续识别,是字符识别的关键问题之一.本文以货运列车车号为例,提出一种有效的分割方法.该方法以弧特征和变基准线区域分割为基础,引入了识别反馈分割策略.将其应用于实际运行的识别系统时获得了较高的正确分割率.     

Efficient algorithms for segmentation of item-set time series

We propose a special type of time series, which we call an item-set time series, to facilitate the temporal analysis of software version histories, email logs, stock market data, etc. In an item-set time series, each observed data value is a set of discrete items. We formalize the concept of an item-set time series and present efficient algorithms for segmenting a given item-set time series. Segmentation of a time series partitions the time series into a sequence of segments where each segment is constructed by combining consecutive time points of the time series. Each segment is associated with an item set that is computed from the item sets of the time points in that segment, using a function which we call a measure function. We then define a concept called the segment difference, which measures the difference between the item set of a segment and the item sets of the time points in that segment. The segment difference values are required to construct an optimal segmentation of the time series. We describe novel and efficient algorithms to compute segment difference values for each of the measure functions described in the paper. We outline a dynamic programming based scheme to construct an optimal segmentation of the given item-set time series. We use the item-set time series segmentation techniques to analyze the temporal content of three different data sets–Enron email, stock market data, and a synthetic data set. The experimental results show that an optimal segmentation of item-set time series data captures much more temporal content than a segmentation constructed based on the number of time points in each segment, without examining the item set data at the time points, and can be used to analyze different types of temporal data.