stroke feature meaning in Chinese
笔划特征
Examples
- Q9 stroke feature q9 stroke example
九方笔划输入例子 - This thesis explains the necessity of the character recognition technology of the computer at first , describe the meaning in which the handwritten numeral discerns ; pretreatment technology of handwritten numeral recognition , including two value , line segmentation , word segmentation smooth , removing noising , standardization and thinning are discussed two value concretely discusses whole threshold value , some threshold value , dynamic threshold value and utilize space information to carry on threshold , which are several kinds of common method of choosing threshold value , especially utilize space information to carry on threshold value is describe in detail ; adopting to the foundation of thinning based on mathematics morphology , thinning algorithm of serials same and thinning algorithm of protecting shape are discussed ; afterwards , according to principle ' s diagram of the on - line character recognition , by analyzing the structure feature of the handwritten numeral , this thesis has proposed the online recognition te chnology of the free handwritten numeral based on the stroke feature and the online recognition technology of the free handwritten numeral based on the multistage classifying device . detail narrated noise removing , stroke characteristic definition and discernment , distance criterion of whole word match ; then under the foundation of handwritten numeral segmentation , off - line handwritten numeral recognition is researched . especially minimum distance classifying device , tree classifying device and adaptive resonance ( art ) network classifying device is discussed at the same time , believes degree analyses are introduced to integrate a lot of classifying devices ; at the end , the typical application of the handwritten numeral recognition was briefly narrated , its application in extensive data statistics , financial affairs , tax , finance and mail sorting have been explored
二值化时对整体阈值二值化、局部阈值二值化、动态阈值二值化和利用空间信息进行阈值选取几种常用的阈值选取方法进行讨论，特别对利用空间信息进行阈值选取进行了详细论述；在对通过对基于数学形态学的细化的基础上，讨论序贯同伦形态细化算法和保形的快速形态细化算法；然后依据联机字符识别原理框图，分析了手写数字的结构特点，提出了基于笔划特征的任意手写数字在线识别技术和基于多级分类器任意手写数字在线识别技术，对其中涉及的笔划识别前的噪声处理、笔划间特征量的定义及识别、整字匹配的距离准则进行了详细叙述；继而在对手写数字的分割的基础下对脱机手写数字识别进行了研究，对基于最小距离分类器字符识别、基于树分类器的字符识别、基于自适应共振( art )网络的字符识别分别进行了详细讨论，并引入置信度分析将多个分类器进行了混合集成；最后简单阐述了手写数字识别的典型应用，对其在大规模数据统计、财务、税务、金融及邮件分拣中的应用进行了探索。