The neural-based segmentation of cursive words using enhanced heuristics
The neural-based segmentation of cursive words using enhanced heuristics
复制标题
DOI：
10.1109/icdar.2005.237
复制
发表时间：
2005-08
期刊：
影响因子：
--
通讯作者：
C. Cheng;M. Blumenstein
中科院分区：
文献类型：
--
作者：
C. Cheng;M. Blumenstein
提出了一种改进的启发式切分器(EHS)和一种改进的基于神经网络的切分技术，分别用于草书切分和切分点验证。EHS采用了两个新功能，结扎检测和神经助手，以定位预期的分割点。然后，除了分割点验证(SPV)输出之外，通过融合从左字符识别输出和中心字符识别输出获得的置信值，改进的基于神经的分割技术可以用于检查预期的分割点。改进的基于神经网络的分割技术使用最近提出的特征提取技术(改进的方向特征)来表示分割点和字符，以增强整体分割过程。EHS和基于神经的分割技术已经实施，并在基准数据库上进行了测试，提供了令人鼓舞的结果。
This paper presents an enhanced heuristic segmenter (EHS) and an improved neural-based segmentation technique for segmenting cursive words and validating prospective segmentation points respectively. The EHS employs two new features, ligature detection and a neural assistant, to locate prospective segmentation points. The improved neural-based segmentation technique can then be used to examine the prospective segmentation points by fusion of confidence values obtained from left and centre character recognition outputs in addition to the segmentation point validation (SPV) output. The improved neural-based segmentation technique uses a recently proposed feature extraction technique (modified direction feature) for representing the segmentation points and characters to enhance the overall segmentation process. The EHS and the neural-based segmentation technique have been implemented and tested on a benchmark database providing encouraging results.