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Text Detection in Natural Images Based on Character Classification

机译:基于字符分类的自然图像文本检测

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Text information in images is very important for image understanding. In this paper, a text location method based on character classification is proposed. The and-valley image (AVI) and the and-ridge image (ARI) are first extracted from the input image. Then character components are detected from the AVI and ARI respectively, and then these components are sent to a character classifier. Finally, text region can be generated by merging all the recognized components. This approach is robust to font style, font size, font color and the background complexity. It is demonstrated in the experiments that our method is efficient.
机译:图像中的文本信息对于理解图像非常重要。提出了一种基于字符分类的文本定位方法。首先从输入图像中提取与谷图像(AVI)和与山脊图像(ARI)。然后分别从AVI和ARI中检测字符成分,然后将这些成分发送到字符分类器。最后,可以通过合并所有识别的组件来生成文本区域。这种方法对于字体样式,字体大小,字体颜色和背景复杂性具有鲁棒性。实验证明,该方法是有效的。

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