一种基于词片识别的字符分割算法

在字符识别领域,对粘连字符的识别是一个被广泛关注的技术难点,而且粘连字符的分割更是产生识别错误的主要原因之一.为了快速准确地进行字符分割,在总结已有方法的特点及不足的基础上,针对电子阅读笔系统的工作特点和实时性要求,提出并实现了一种面向电子阅读笔系统的基于词片识别的分割算法.该方法由于通过对字母组合的识别,降低了传统的基于孤立字符识别方法对于字符切分的要求,而且以中心生长法和改进的峰谷函数为切分工具来进行字符分割,简单实用,因而其在减少因粘连字符切分错误引起的识别错误的同时,不仅降低了运算复杂度,而且适合在阅读笔等嵌入式设备上应用.实验证明,该算法不仅效率高,而且实现简单,还能够降低分割错误带来的识别错误.

An Optimal Character Segmentation Algorithm Based on Connected Component Recognition

Segmentation of merged characters is one of difficulties that have attracted a great deal of attention in optical character recognition(OCR).Nowadays,unsuitable segmentation is the primary cause of recognition errors.Based on the analysis of the shortcomings of some traditional algorithms for printed character segmentation,we notice that it is necessary to propose a fine method to meet with the requirement of real time processing and the characteristics of DSP module including relative low power and small memory comparing with PC.In this paper a new algorithm of segmentation and recognition based on connected component is proposed which can be used for electronic reading-pen.The proposed method reduces computation time by recognizing the connected component as a whole.It segments connected component by middle expansion method and peak-paddle function.As a result,recognition error arose by segmentation error can be reduced.Experiment results have proved that the algorithm is effective,easy to implement and it is reasonable and applicable for to ERpen.