Auto scene text detection based on edge and color features

Xiaodong Huang, Kehua Liu, Lishang Zhu
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引用次数: 10

Abstract

In this paper we present a novel approach to detecting scene text based on the edge and color features. Firstly, because the character edge feature is not sensitive to the luminance changes, we extract the edge features to locate the candidate text region coarsely. Secondly, according to the text row character will keep similar color, we use the K-means clustering to extract color feature and locate the candidate text regions accurately. Finally, we use a trained SVM classifier to distinguish the text region from non-text region in these candidate regions. Experimental results show that our algorithm performs well for detecting scene text with various color, font-size and text alignment.
基于边缘和颜色特征的自动场景文本检测
本文提出了一种基于边缘和颜色特征的场景文本检测方法。首先,由于字符边缘特征对亮度变化不敏感,提取边缘特征进行粗定位;其次,根据文本行字符保持相似颜色的特点,采用k均值聚类方法提取颜色特征,准确定位候选文本区域;最后,我们使用训练好的SVM分类器在这些候选区域中区分文本区域和非文本区域。实验结果表明,该算法能够很好地检测不同颜色、字体大小和文本对齐方式的场景文本。
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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