基于颜色和笔画特征的文本分割算法

Text Segmentation Using Color and Stroke Features

自动提取图像中的文本对图像视频检索具有重要意义。提出了一种基于颜色和笔画特征,应用无监督聚类方法进行复杂背景下的文本分割算法。首先在对文本行图像增强的基础上,应用颜色约减和直方图确定文本颜色。然后提取颜色和笔画特征,应用k-均值聚类算法分割出文本和背景像素。最后应用后处理优化分割结果。实验表明,该算法具有较好的分割效果。

A novel text segmentation approach based on unsupervised clustering using color and stroke features was presented. Firstly, the possible text and background color is estimated on the enhanced text line image by color reduction and histogram calculation. Then color and stroke features were extracted and text and background pixels are determined by K-mean clustering algorithm. At last, segmentation result is optimized by post-processing. The performance of our approach is demonstrated by experimental results for a set of images with Chinese and English text.