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基于连通分量特征的文本检测与分割

DOI: 10.11834/jig.2006011285

Keywords: 级联分类器,两阶段分类,文本检测,文本特征

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Abstract:

自然背景中的文本识别具有巨大的应用价值,但其应用却一直受到文本检测和分割技术的限制。为了更有效地进行文本检测与分割,提出了一种基于连通分量特征的自然场景中文本检测分割算法。该算法首先将原始图片通过Niblack方法分解为许多连通分量;接着,用一个级联分类器和一个SVM组成的两阶段分类模块来验证这些连通分量的文本特征。由于文本连通分量和非文本连通分量在特征上存在差异,大多数非文本会被级联分类器丢弃,而SVM则能在此结果上做进一步的验证,因此最终输出只有文本的二值图像。最后用该算法在测试数据上进行了评估实验,评估结果表明,检测精度超过90%,响应超过93%。

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