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基于文本像素颜色聚类的场景文本检测算法

Scene Text Detection Algorithm Based on Color Clustering of Textual Pixels

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摘要

提出了一种基于文本像素颜色聚类的场景文本检测方法。利用最大稳定极值区域算法提取原图像初始文本区域,并通过笔画宽度变换算法与角度特征筛选稳定文本像素。在稳定文本像素中进行多尺度颜色聚类,并结合支持向量机进行了字符区域验证,最后进行文本行聚合,实现文本检测的目标。分别在公共数据集ICDAR2011和ICDAR2013上进行测试,算法的F-score分别为0.76和0.77,相比其他文本检测算法,所提算法获得了较好的检测性能。

Abstract

A scene text detection method based on color clustering of textual pixels is proposed, in which the initial textual regions of original images are extracted by the maximally extremal stable regional algorithm, and the stable textual pixels are screened out by the stroke width transform algorithm and the angle features. The multi-scale color clustering is conducted in these stable textual pixels, which is combined with a support vector machine for the realization of character regional verification. The text line aggregation is finally adopted to achieve the goal of text detection. The tests are conducted on two public datasets of ICDAR2011 and ICDAR2013, and the F-scores of this algorithm are 0.76 and 0.77, respectively. Compared with the existing text detection methods, the proposed method obtains a good text detection performance.

Newport宣传-MKS新实验室计划
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中图分类号:TP391.4

DOI:10.3788/lop56.071006

所属栏目:图像处理

基金项目:国家自然科学基金(61303028)

收稿日期:2018-09-03

修改稿日期:2018-10-10

网络出版日期:2018-10-30

作者单位    点击查看

李敏:武汉理工大学信息工程学院, 湖北 武汉 430070
郑建彬:武汉理工大学信息工程学院, 湖北 武汉 430070
詹恩奇:武汉理工大学信息工程学院, 湖北 武汉 430070
汪阳:武汉理工大学信息工程学院, 湖北 武汉 430070

联系人作者:詹恩奇(eqzhan@whut.edu.cn)

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引用该论文

Li Min,Zheng Jianbin,Zhan Enqi,Wang Yang. Scene Text Detection Algorithm Based on Color Clustering of Textual Pixels[J]. Laser & Optoelectronics Progress, 2019, 56(7): 071006

李敏,郑建彬,詹恩奇,汪阳. 基于文本像素颜色聚类的场景文本检测算法[J]. 激光与光电子学进展, 2019, 56(7): 071006

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