A maximally stable extremal region based scene text localization method

Chengqiu Xiao; Lixin Ji; Chao Gao; Shaomei Li

doi:10.1117/12.2196999

6 July 2015 A maximally stable extremal region based scene text localization method

Chengqiu Xiao, Lixin Ji, Chao Gao, Shaomei Li

Proceedings Volume 9631, Seventh International Conference on Digital Image Processing (ICDIP 2015); 96311Y (2015) https://doi.org/10.1117/12.2196999
Event: Seventh International Conference on Digital Image Processing (ICDIP15), 2015, Los Angeles, United States

Abstract

Text localization in natural scene images is an important prerequisite for many content-based image analysis tasks. This paper proposes a novel text localization algorithm. Firstly, a fast pruning algorithm is designed to extract Maximally Stable Extremal Regions (MSER) as basic character candidates. Secondly, these candidates are filtered by using the properties of fitting ellipse and the distribution properties of characters to exclude most non-characters. Finally, a new extremal regions projection merging algorithm is designed to group character candidates into words. Experimental results show that the proposed method has an advantage in speed and achieve relatively high precision and recall rates than the latest published algorithms.

Citation Download Citation

Chengqiu Xiao, Lixin Ji, Chao Gao, and Shaomei Li "A maximally stable extremal region based scene text localization method", Proc. SPIE 9631, Seventh International Conference on Digital Image Processing (ICDIP 2015), 96311Y (6 July 2015); https://doi.org/10.1117/12.2196999

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