Connected character recognition in cursive handwriting using selective attention model with bend processing
Connected character recognition in cursive handwriting using selective attention model with bend processing
复制标题
使用选择性注意模型和弯曲处理的草书连接字符识别
DOI：
10.1002/scj.4690261004
复制
发表时间：
1994
期刊：
影响因子：
--
通讯作者：
K. Fukushima
中科院分区：
文献类型：
--
作者：
Hayaru Shouno;K. Fukushima
Imagawa等人提出了一种具有选择性注意机制的系统，作为识别草书手写体英文连字符序列的系统之一。然而，Imagawa等人的系统并没有很高的识别能力。它是一个相对较小的系统，待识别的字符类别由5个字符组成。本研究对Imagawa等人提出的识别系统进行了扩展，构建了一个具有更高识别能力的系统。其中一位作者指出，选择性注意模型的一部分类似于模式识别系统neocognitron。对于新认知器，有报道称通过引入弯曲检测电路提高了其识别能力。因此，作者构建了一个系统，其中弯曲处理电路由Imagawa等人引入到系统中。对所构建的系统进行了多种测试模式，并通过计算机仿真验证了所提出的系统在手写体连接字符序列识别方面的有效性。
As one of the systems to recognize the cursive handwritten English connected character sequence, Imagawa et al. proposed a system with the selective attention mechanism. The system of Imagawa et al., however, does not have a very high recognition ability. It is a relatively small-scale system, where the character category to be recognized is composed of 5 characters. This study extends the recognition system proposed by Imagawa et. al., and a system with a higher recognition ability is constructed. One of the authors notes that a part of the model for selective attention is similar to the pattern recognition system neocognitron. With respect to the neocognitron, it is reported that the recognition ability is improved by introducing the bend detection circuit. Consequently, the authors constructed a system, where the bend processing circuit is introduced into the system by Imagawa et al. Various test patterns are given to the constructed system, and it is verified by executing a computer simulation that the proposed system is effective in the recognition of the handwritten connected character sequence.