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Text String Extraction from Scene Image Based on Edge Feature and Morphology

机译:基于边缘特征和形态的场景图像提取文本字符串

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Extraction of text from scene image is much difficult than extraction from simple document image. A lot of researches succeeded in extracting single text string from image, but can not deal with image including many text strings. Meanwhile, the result may be mixed with noises be similar to text. This paper describes an algorithm that uses mathematical morphology to extract text effectively, and edge border ratio is utilized to differentiate text region from noise region, using the edge contrast feature of the text region in real scene. This paper also describes the method which can connect characters into text strings, and distribute text strings to different subimages according to their width of strokes. The algorithm is implied to scene image like signs, indicators as well as magazine covers, and its robustness is proved.
机译:从场景图像提取文本比简单文档图像的提取很大。大量研究成功地从图像中提取单个文本字符串,但不能处理包括许多文本字符串的图像。同时,结果可以与噪声混合类似于文本。本文介绍了一种使用数学形态学有效提取文本的算法,并且利用边缘边界比来利用实际场景中文本区域的边缘对比度来区分来自噪声区域的文本区域。本文还描述了可以将字符连接到文本字符串中的方法,并根据其笔划的宽度将文本字符串分发给不同的子程。该算法暗示到场景图像,如符号,指示器以及杂志封面,并证明其鲁棒性。

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