摘要： 中文联机手写文本切分识别要求预合并快速高效。为此，设计一个基于最小风险的多层次线性分类器。该分类器根据笔画及切分块的几何特征，采用分层合并的方式完成预合并过程。通过对联机样本进行的实验证明，该分类器保持欠切分错误率在一个较低水平的同时，有效地控制了过切分的错误率。
关键词:
字符切分,
预合并,
最小风险,
鉴别学习,
多层次分类器
Abstract: To solve the problem that high speed and effectiveness is needed for the pre-merger step of online Chinese handwritten text recognition, a multi-layer linear classifier based on minimum risk is provided and realized, which utilizes the geometrical features of strokes and segmented blocks and introduces the scheme of multi-layer combination. Experiments running on real samples show that the classifier reduces the over-segmentation error rate significantly while keeping the under-segmentation error rate in a very low level.
Key words:
character segmentation,
pre-merger,
minimums risk,
discriminative learning,
multi-layer classifier
中图分类号:
姚正斌, 丁晓青, 刘长松. 基于分类的中文联机手写文本预合并方法[J]. 计算机工程, 2011, 37(19): 138-140.
TAO Zheng-Bin, DING Xiao-Jing, LIU Chang-Song. Pre-merger Method of Chinese Online Handwritten Text Based on Classification[J]. Computer Engineering, 2011, 37(19): 138-140.