基于滴水算法的验证码中粘连字符分割方法

众多研究表明，如果能将验证码中的字符分割开来，用现有的机器学习算法一般都能取得比较好的识别效果。针对字符粘连情况下的验证码的识别问题，提出了一种粘连字符的分割方法。该方法将字符的宽度统计值和竖直投影直方图中的投影极小值点相结合找到分割点，以这些分割点作为滴水算法的起始滴落点对粘连字符进行分割。实验结果证明，该方法用于分割验证码中的粘连字符具有一般性，能够提高验证码识别率。

Segmentation method for merged characters in CAPTCHA based on drop fall algorithm

Many researches demonstrate that good result can be gained by existing machine learning algorithms in the recognization of CAPTCHA（Completely Automated Public Turing test to tell Computers and Humans Apart）if single characters can be split. A method is presented to segment the merged characters in the recognization of CAPTCHA with touching characters. It seeks division points by combining the statistics of character width and the vertical histogram pro-jection minimums, and then uses these points as the starting points of the drop fall algorithm to segment merged charac-ters in CAPTCHA. The experiments show that it is a general method and can improve the recognization rate.