基于蚂蚁聚类的自然场景图像文本检测

P. Tomer, Ajay Goyal
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引用次数: 2

摘要

自然场景中的文本图片是场景理解、基于内容的图像检索、辅助导航和自动地理编码等基于图像的应用的必要线索。然而,从具有多种颜色的花哨环境中定位文本可能是一项艰巨的任务。尽管在自然场景中有各种各样的技术用于文本的检测。本文实现的工作(基于结构的分割和分组从自然场景中检测文本字符串)是基于基于梯度的分割和基于颜色的分割,但这里实现的技术效率较低,错误率更高,因此准确性较低。而本文实现的自然场景文本检测技术是基于Ant聚类的。通过使用Ant聚类,提高了文本检测技术的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ant clustering based text detection in natural scene images
Text pictures in natural scene are necessary clues for several image-based applications like scene understanding, content-based image retrieval, helpful navigation, and automatic geocoding. However, locating text from a fancy atmosphere with multiple colors may be a difficult task. Although there are various techniques implemented for the detection of the text in natural scenes. The work implemented in paper(Text string detection from natural scenes by structural based partition and grouping) is based on Gradient based Partition and Color based Partition but the techniques implemented here provides less efficiency and the chances of error rate is more hence have less accuracy. But the technique implemented in this paper for the detection of texts in natural scenes is based on Ant based clustering. By using Ant clustering the performance of the technique for the detection of text has been increased.
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