Book Reviews

Gillies, Donald, Artificial Intelligence and Scientific Method
Gurney, Kevin, An Introduction to Neural Networks     

Extraction of delta-lognormal parameters from handwriting strokes

In the context of the Kinematic Theory of Rapid Human Movement, handwriting strokes are considered to be primitives that reflect the intrinsic properties of the neuromuscular system of a writer as well as the basic control strategies that the writer uses to produce such strokes. The study of these strokes relies on the extraction of the different parameters that characterize a stroke velocity profile. In this paper, we present a new method for stroke parameter extraction. The algorithm is described and evaluated under various testing conditions.     

A computer-based system to support forensic studies on handwritten documents

Computer-based forensic handwriting analysis requires sophisticated methods for the pre-processing of digitized paper documents, in order to provide high-quality digitized handwriting, which represents the original handwritten product as accurately as possible. Due to the requirement of processing a huge amount of different document types, neither a standardized queue of processing stages, fixed parameter sets nor fixed image operations are qualified for such pre-processing methods. Thus, we present an open layered framework that covers adaptation abilities at the parameter, operator, and algorithm levels. Moreover, an embedded module, which uses genetic programming, might generate specific filters for background removal on-the-fly. The framework is understood as an assistance system for forensic handwriting experts and has been in use by the Bundeskriminalamt, the federal police bureau in Germany, for two years. In the following, the layered framework will be presented, fundamental document-independent filters for textured, homogeneous background removal and for foreground removal will be described, as well as aspects of the implementation. Results of the framework-application will also be given. Received July 12, 2000 / Revised October 13, 2000     

A High Speed VLSI Architecture for Handwriting Recognition

This article presents PAPRICA-3, a VLSI-oriented architecture for real-time processing of images and its implementation on HACRE, a high-speed, cascadable, 32-processors VLSI slice. The architecture is based on an array of programmable processing elements with the instruction set tailored to image processing, mathematical morphology, and neural networks emulation. Dedicated hardware features allow simultaneous image acquisition, processing, neural network emulation, and a straightforward interface with a hosting PC.HACRE has been fabricated and successfully tested at a clock frequency of 50 MHz. A board hosting up to four chips and providing a 33 MHz PCI interface has been manufactured and used to build BEATR IX, a system for the recognition of handwritten check amounts, by integrating image processing and neural network algorithms (on the board) with context analysis techniques (on the hosting PC).     

基于PXA250的GPS,T-DMB智能手机方案实现

GPS,T-DMB功能现今已成为手机新功能应用的热点.从GPS技术、T-DMB技术和GSM等各功能模块的特点出发,介绍了一种低成本、多功能的智能手机的设计方案.在该手机方案设计上,充分利用PXA250的强大的处理能力,较简便地实现了GPS导航功能以及T-DMB电视接收功能,并阐述该款产品的硬件设计和软件设计实现.从优化软硬件设计的角度阐述如何以较低的成本来实现几项高端的手机功能.     

笔迹鉴别预处理算法的设计与实现

笔迹鉴别是身份鉴别技术中的一种有效方法.作者深入细致的研究了笔迹鉴别中的各种预处理算法,对其中一些传统的处理方法提出了改进方案,以vc++6.0为开发平台通过大量的实验进行了验证,实验表明提出的算法具有处理效果好、可行性强、速度快等一系列的优点,用63副样本做对比实验,新方法可以提高笔迹鉴别率9%左右,其在笔迹鉴别、车辆识别、地理信息系统等图像处理领域都有较好的应用价值.     

利用拓扑关系的图形识别方法研究

本方法利用图的同构算法对具有拓扑湾性的图形进行识别,它可以应用于限制性手写字符识别等领域。该方法具有算法简单、正确识别率较高等特点,本文介绍了该方法的原理及其应用。     

基于隐马尔可夫模型的3D手写识别方法

为实现便捷高效的人机交互,提高交互能力,在基于隐马尔可夫模型(HMM)的基础上,提出了一种新的3D手写识别方法。该方法使用带有三轴加速度传感器的手持设备去采集各种手写数据;使用插值及快速傅里叶变换(FFT)滤波等方法对采集的数据进行预处理;使用隐马尔可夫模型对每个手写动作进行模型训练;使用训练过的手写模型对采集的数据进行手写识别。数据测试结果表明,该方法在手持移动设备上数据分类的准确性可达到84.5%。     

基于函数参量的手写签名比较方法

本文介绍了一种基于函数参量的点一点手写签名匹配映射方法,首先对两个待比较的签名进行特殊点匹配,然后利用得到的对应特殊点序列将两签名分段,接着每一对相应笔段中的点级由点－点映射算法得到最后的匹配映射结果。     

手写运动的协作基元合成分析方法

研究一种生物运动神经控制机理与数据合成分析相结合的手写运动分析方法.特别地,将运动协作基元的概念用于手写运动数据分析,研究手写运动的协作基元合成分析方法,建立符合生物运动神经控制规律的手写运动数据理解模式.提出的协作基元合成分析过程由2个交替迭代的优化算法组成:其一,基于非负矩阵因子分解模式估计协作基元及调制幅度;其二,采用相似性最大化准则估计协作基元的激活时间.针对笔画切分的实验研究表明,采用协作基元合成分析方法获得的笔画切分结果,能够很好揭示相邻笔画之间的重叠连接模式,证实了所提方法的有效性.