Graph-Based Text Segmentation Using a Selected Channel Image

Chao Zeng, W. Jia, Xiangjian He, Jie Yang
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引用次数: 1

Abstract

This paper proposes a graph-based method for segmentation of a text image using a selected colour-channel image. The text colour information usually presents a two polarity trend. According to the observation that the histogram distributions of the respective colour channel images are usually different from each other, we select the colour channel image with the histogram having the biggest distance between the two main peaks, which represents the main foreground colour strength and background colour strength respectively. The peak distance is estimated by the mean-shift procedure performed on each individual channel image. Then, a graph model is constructed on a selected channel image to segment the text image into foreground and background. The proposed method is tested on a public database, and its effectiveness is demonstrated by the experimental results.
使用选定通道图像的基于图形的文本分割
本文提出了一种基于图的方法,使用选定的颜色通道图像对文本图像进行分割。文本色彩信息通常呈现两极性趋势。根据观察到各颜色通道图像的直方图分布通常是不同的,我们选择直方图中两个主峰之间距离最大的颜色通道图像,分别代表主要的前景色彩强度和背景色彩强度。峰值距离通过对每个单独通道图像执行的均值移位程序估计。然后,在选定的通道图像上构建图形模型,将文本图像分割为前景和背景;在一个公共数据库上对该方法进行了测试,实验结果证明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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