共查询到19条相似文献,搜索用时 140 毫秒
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提出了一种提取汉字笔段的新方法。从形态学骨架算法生成的骨架点出发,通过分析骨架点的半径分布及不同半径骨架点的位置,发现了笔段提取中产生的毛刺和畸变与骨架点半径之间的规律,进而以此规律为基础提出了一种克服毛刺和畸变的汉字笔段提取方法,最后给出了手写体和印刷体汉字笔段提取的实验结果。实验表明,该方法是行之有效的。 相似文献
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手写印刷体汉字的笔段抽取及偏旁识别 总被引:1,自引:1,他引:0
本文采用对汉字点阵图象进行方向变换的方法抽取汉字的笔段, 采用结构分析的方法识别分布于汉字四周的偏旁, 对国标一级汉字中的99类偏旁计一万余字进行了偏旁抽取试验, 当侯选偏旁数<5时, 累计正确侯补率>96%。 相似文献
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借鉴仿生模式识别的认知观点,从汉字的构造机理和人类认识汉字的习惯角度出发,提出一种基于小波变换的图像汉字识别方法。制定了图像汉字笔划特征提取的具体规则,采用小波变换的方法对图像汉字边缘和笔划轮廓进行检测,通过有效提取图像汉字笔段信息,进行笔段合成,生成汉字或汉字的基本笔划。仿真实验结果表明,这种方法提高了图像汉字笔划特征提取的准确率和稳定性,对于印刷体和书写较规范的手写体图像汉字具有极高的识别率。 相似文献
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提出一种利用过程神经元网络,对脱机手写体汉字二维图像的笔段提取方法。定义了脱机手写体汉字笔段的提取方法,给出了用于脱机手写体汉字笔段提取的过程神经网络的模型和学习算法,并对算法进行了仿真实验。该方法与其他汉字笔段提取方法相比,具有速度快、可学习、鲁棒性好的特点。经实验证明,该方法是行之有效的。 相似文献
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HU Hui-yu 《数字社区&智能家居》2008,(32)
笔段型液晶显示器是以长条状显示像素组成一位显示字符或专用固定图形和字符的液晶显示器。该文介绍由HOLTEK HT1621 LCD驱动器与液晶显示板构成的笔段型液晶显示模块在便携式测力计中的应用,其中包括硬件电路设计及控制程序设计。 相似文献
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本文以16*16点阵的基础点阵为例,说明嵌入点阵汉字的实现机理与方法,并给出了汉字点阵的程序提取方法,及利用该汉字点阵实现嵌入式点阵汉字显示应用的两个C语言程序示例。 相似文献
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中国女书是具有鲜明民族特色的文字,目前国内还没有公认的女书规范字库。针对手写体文字规范化字体生成过程多采用人工修正方式、效率低下的现状,该文设计了一种女书手写字符规范字自动生成方法。基于手写文字样本,提取其单像素骨架,并结合字符轮廓信息进行骨架畸变点校正;然后提取骨架特征点和笔段,根据笔段连通性和交角情况建立笔段关联矩阵;基于笔段关联矩阵由笔段恢复笔画,获取笔画路径关键点序列;最后基于三次Bezier曲线重绘字符笔画并均匀加粗,形成笔画粗细一致、平滑无毛刺、无畸变的规范字体。实验结果表明,该方法自动便捷,效果良好,效率优于人工方式,经改进后可以推广到其他手写字符的规范化过程。 相似文献
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一种笔段序列匹配联机汉字识别方法 总被引:4,自引:0,他引:4
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 相似文献
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A novel stroke-based feature extraction for handwritten Chinese character recognition 总被引:7,自引:0,他引:7
A stroke-based approach to extract skeletons and structural features for handwritten Chinese character recognition is proposed. We first determine stroke directions based on the directional run-length information of binary character patterns. According to the stroke directions and their adjacent relationships, we split strokes into stroke and fork segments, and then extract the skeletons of the stroke segments called skeleton segments. After all skeleton segments are extracted, fork segments are processed to find the fork points and fork degrees. Skeleton segments that touch a fork segment are connected at the fork point, and all connected skeleton segments form the character skeleton. According to the extracted skeletons and fork points, we can extract primitive strokes and stroke direction maps for recognition. A simple classifier based on the stroke direction map is presented to recognize regular and rotated characters to verify the ability of the proposed feature extraction for handwritten Chinese character recognition. Several experiments are carried out, and the experimental results show that the proposed approach can easily and effectively extract skeletons and structural features, and works well for handwritten Chinese character recognition. 相似文献
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目的 研究手写汉字图像时,骨架是最为常见的切入点之一。利用传统细化算法提取手写汉字骨架,容易在笔画交叉等情况复杂的区域产生形变。针对此问题,提出一种基于局部关联度的手写汉字骨架提取算法。方法 首先对手写汉字图像进行细化以获取原始骨架,按照端点、普通点和复杂点3种类别标注骨架点;利用8邻域窗口扫描相互连通的复杂点,检测并提取复杂区域;删除复杂区域,将原始骨架拆分为若干简单笔画段,形变部分在此过程中被一并移除;提取局部子段,根据笔画段间的方向差异程度和曲率变化程度,计算局部关联度;制定一种局部关联度最优的连接策略,对满足连接条件的笔画段进行插值补偿,从而修正形变,并得到完整的汉字骨架。结果 对于600个实验样本,从骨架直接检测复杂区域所得结果十分接近理想情况,而轮廓法所得数量是理论值的2.5倍;基于局部关联度重组笔画段,绝大多数形变得到修正,重组后的骨架符合真实拓扑结构;以标准骨架为参考,骨架提取准确率达到了98.41%。结论 局部关联度最优的手写汉字骨架提取算法,能够有效检测复杂区域,对形变具有良好的修正作用,提取所得骨架能够正确反映复杂笔画间的位置结构关系,是一种实用有效的骨架提取方法。 相似文献
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In this article, a stroke-based neuro-fuzzy system for off-line recognition of handwritten Chinese characters is proposed. The system consists of three main components: stroke extraction, feature extraction, and recognition. Stroke extraction applies a run-length-based method to extract strokes from the image of a given character. Various fuzzy features of the extracted strokes, including slope, length, location, and cross relation, are obtained by the feature extraction module. An ART-based neural network, using a two-stage training algorithm, is used to recognize characters. This system extracts strokes in only two passes, and is free from the presence of spurious and thick strokes. The neural model used provides a fast convergence rate. Nodes are allowed to be shared to reduce the size of the resulting network. Features need not be classified in advance by the user. Furthermore, the architecture of the network is self-constructed without the intervention of the user. Experiments have shown that this system is effective. 相似文献
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Model-based stroke extraction and matching for handwritten Chinese character recognition 总被引:11,自引:0,他引:11
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. 相似文献
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基于可伸缩矢量图SVG的在线手写汉字是以SVG图像作为汉字图像格式、以SVG的path对象作为笔画的基本存储单元来对汉字进行显示和存储的,笔画的轮廓是以手写过程中记录的坐标值作为特征数值加以确定的。基于此种SVG手写汉字存储和表示形式,本文提出一种基于图论的在线连续手写汉字多步分割方法。该方法根据汉字笔画间的坐标位置关系对手写笔画序列构建无向图模型,并利用图的广度优先搜索将原笔画序列分割为互不连通的笔画部件,使偏旁部首分离较远、非粘连汉字得到正确分割;然后利用改进的tarjan算法对部件中的粘连字符进行分割,最后基于笔画部件间距,利用二分类迭代算法对间距进行分类,找出全局最佳分割位置,对过分割的部件进行重组合并。实验结果表明,该方法对于在线手写汉字的分割是有效可行的。 相似文献