Efficient Text Localization in Born-Digital Images by Local Contrast-Based Segmentation

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	Efficient Text Localization in Born-Digital Images by Local Contrast-Based Segmentation
	Kai Chen; Yin, Fei; Liu, Chenglin
	2015-08
会议日期	2015-8
会议地点	法国南锡
关键词	Text Localization Image Segmentation Local Contrast Connected Components Grouping
英文摘要	Text localization in born-digital images is usually performed using methods designed for scene text images. Based on the observation that text strokes in born-digital images mostly have complete contours and the pixels on the contours have high contrast compared with the adjacent non-text pixels, we propose a method to extract candidate text components using local contrast. First, the image is segmented into smooth and non-smooth regions. After removing non-text smooth regions, the remaining smooth regions are merged with non-smooth regions to form a candidate text image, which is binarized into high-value and low-value connected components (CCs). The CCs undergo CC filtering, line grouping and line classification to give the text localization result. Experimental results on the born-digital dataset of ICDAR2013 robust reading competition demonstrate the efficiency and superiority of the proposed method.
会议录	International Conference on Document Analysis and Recognition (ICDAR)
内容类型	会议论文
源URL	[http://ir.ia.ac.cn/handle/173211/11948]
专题	自动化研究所_模式识别国家重点实验室_模式分析与学习团队
通讯作者	Kai Chen
作者单位	中科院自动化研究所
推荐引用方式 GB/T 7714	Kai Chen,Yin, Fei,Liu, Chenglin. Efficient Text Localization in Born-Digital Images by Local Contrast-Based Segmentation[C]. 见:. 法国南锡. 2015-8.