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A Study for High Performance Character Extraction from Color Scene Images

机译:彩色场景图像高性能字符提取研究

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This paper describes a method for extracting character strings from scene images. Most characters on scene images appear with the same color and font size at every word or text line. In our algorithm, a scene image is divided into several blocks based on edges in the color space at first. Then the blobs, which consist of similar color pixels, are extracted by a clustering in a color space for each block. Although these blobs are correspond to characters or background patterns, after connecting them using these aspect ratios and pitches, SVM (Support Vector Machine) on several textural features of these blobs will classify each connected blob into character or background patterns. Testing with 251 images from ICDAR 2003 Text Locating Competition shows effectiveness of our algorithm.
机译:本文介绍了一种从场景图像中提取字符串的方法。场景图像上的大多数字符以每个单词或文本行的颜色和字体大小出现。在我们的算法中,现场图像首先基于颜色空间中的边缘划分为几个块。然后由每个块的颜色空间中的聚类提取,该斑点由相似的颜色像素提取。虽然这些斑点对应于字符或背景图案,但在使用这些宽高比和音高的连接之后,SVM(支持向量机)在这些BLOB的若干纹理特征上将分类为字符或背景模式。使用ICDAR 2003文本的251张图片测试显示竞争显示了我们算法的有效性。

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