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

Yuming Wang, Naoki Tanaka
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引用次数: 17

Abstract

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.
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基于边缘特征和形态学的场景图像文本字符串提取
从场景图像中提取文本比从简单的文档图像中提取文本要困难得多。许多研究成功地从图像中提取了单个文本字符串,但不能处理包含多个文本字符串的图像。同时,结果可能会混入与文本相似的噪声。本文描述了一种利用数学形态学有效提取文本的算法,利用真实场景中文本区域的边缘对比度特征,利用边缘边缘比来区分文本区域和噪声区域。本文还介绍了将字符连接成字符串,并根据笔画宽度将字符串分配到不同子图像的方法。将该算法应用于标志、指标、杂志封面等场景图像,证明了该算法的鲁棒性。
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