基于主动轮廓模型的文本检测方法

针对复杂背景下的文本检测问题,提出了一种基于主动轮廓模型的文本检测方法.输入的图像首先经过so-bel-laplacian锐化后再由gaussian-laplacian进行过滤.预处理完成后的图片首先通过改进的主动轮廓模型得到初始轮廓,再通过算法的反复迭代扩大或缩小轮廓线得到最终轮廓,最后通过后处理尽量排除非文本块,从而得到最终文本区.区别于以往检测方法,所提方法最终不但可以框出文本行,还可以框出单个文本,有利于后续分割识别的进行.实验表明所提方法可有效检测出图像中的文本.

Text Detection Method Based on Active Contour Model

To detect text from images with different backgrounds,a text detection method with active contour models was proposed.Before text detection,the sobel-laplacian and gaussian-laplacian were used to sharpen edges and smooth noise,and then iteration algorithm was repeated to enlarge or lessen the contour to get the final contour,ruling out the un-text block at last.The proposed method can box a single text eventually,and it is advantageous to the subsequent segmentation recognition.Experiment shows that the proposed method can effectively detect the text in the image.