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Recording medium handwritten character recognition method, handwriting recognition system, and handwriting recognition program

机译:记录介质手写字符识别方法,手写识别系统和手写识别程序

摘要

It is possible to perform character recognition performance and easy even for input that was written stroke such as regular script when performing handwriting recognition and online handwriting recognition, and also addresses the conversion of such significant rotational deformation and . And captured by the parameter representation in each fraction for each handwriting entered performs piecewise linear approximation to each image in each, as a vector reaching the end point from the starting point, the present invention includes a reference, each broken line, which is piecewise linear approximation that for this The winding the sum of the external angles of the same sign, which is obtained as a line angle series angle formed between each polygonal line with the axis that is, to obtain the external angle series of corner vertices of the polygonal line obtained, the same plus or minus sign of the exterior angle series is continuous The the angle sequence, features and global by its respective sequence obtained, extracted sharing manner and hierarchical, local features in the curved portion which are divided according to the series winding angle, the quasi-local features, the In comparing the extraction results, with the template site of the recognition target character which is prepared in advance, I have to perform the character recognition.
机译:即使在执行手写识别和在线手写识别时,甚至对于常规笔迹之类的笔画输入,也可以实现字符识别性能,并且操作简便,并且还解决了这种明显的旋转变形和转换问题。并且对于输入的每个笔迹,由参数表示法捕获在每个分数中的每个分数执行分段线性逼近,作为从起点到达终点的矢量,本发明包括参考,每个虚线都是分段线性的对此的近似计算方法是缠绕相同符号的外角之和,该外角的总和是通过在每条多角形线与轴之间形成的线角序列角而获得的,即,获得该多角线的角顶点的外角序列所获得的外角序列的相同的​​正负号是连续的。角序列,特征和整体按其各自的序列获得,提取的共享方式和弯曲部分中分层的局部特征,根据序列缠绕角度进行划分,拟局部特征,在比较提取结果时,与识别目标字符的模板位置wh ich是事先准备好的,我必须执行字符识别。

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