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research-article

Robust text detection via multi-degree of sharpening and blurring

Authors:

Wenbin HuAuthors Info & Claims

Signal Processing, Volume 124, Issue C

Pages 259 - 265

https://doi.org/10.1016/j.sigpro.2015.06.025

Published: 01 July 2016 Publication History

Abstract

Text detection is an important process for many content-based image analysis tasks. In this paper, we propose an approach to scene text detection via multi-degree of sharpening and blurring. Input image is sharpened and blurred with unsharp masking (USM) and bilateral filter. Then components are extracted with Maximally Stable Extremal Regions (MSER) from origin and processed images. Color, spatial layout and distance features of component are calculated, and features are weighted to construct the text candidates with distance function where the weights of features were trained before. At last, text candidates are estimated with a character classifier and the non-text candidates are eliminated. Experiments show that the proposed approach is robust to complex backgrounds and low image quality. We apply multi-degree sharpening and blurring before component extraction.Color, spatial layout and distance features are extracted to construct text candidates.Recall figure will increase if more preprocesses are applied.Multi-degree preprocesses perform well when dealing with complex backgrounds and low image quality.

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Cited By

Yang KYi JChen AJin Z(2024)Buffer-textEngineering Applications of Artificial Intelligence10.1016/j.engappai.2023.107774130:COnline publication date: 1-Apr-2024
https://dl.acm.org/doi/10.1016/j.engappai.2023.107774
Li MBai MLv Y(2022)Text segmentation by integrating hybrid strategy and non-text filteringMultimedia Tools and Applications10.1007/s11042-022-13029-181:30(44505-44522)Online publication date: 1-Dec-2022
https://dl.acm.org/doi/10.1007/s11042-022-13029-1
Xue MShivakumara PZhang CLu TPal U(2019)Curved text detection in blurred/non-blurred video/scene imagesMultimedia Tools and Applications10.1007/s11042-019-7721-278:18(25629-25653)Online publication date: 1-Sep-2019
https://dl.acm.org/doi/10.1007/s11042-019-7721-2
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Information & Contributors

Information

Published In

cover image Signal Processing

Signal Processing Volume 124, Issue C

July 2016

275 pages

ISSN:0165-1684

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Copyright © Elsevier B.V.

Publisher

Elsevier North-Holland, Inc.

United States

Publication History

Published: 01 July 2016

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Cited By

Yang KYi JChen AJin Z(2024)Buffer-textEngineering Applications of Artificial Intelligence10.1016/j.engappai.2023.107774130:COnline publication date: 1-Apr-2024
https://dl.acm.org/doi/10.1016/j.engappai.2023.107774
Li MBai MLv Y(2022)Text segmentation by integrating hybrid strategy and non-text filteringMultimedia Tools and Applications10.1007/s11042-022-13029-181:30(44505-44522)Online publication date: 1-Dec-2022
https://dl.acm.org/doi/10.1007/s11042-022-13029-1
Xue MShivakumara PZhang CLu TPal U(2019)Curved text detection in blurred/non-blurred video/scene imagesMultimedia Tools and Applications10.1007/s11042-019-7721-278:18(25629-25653)Online publication date: 1-Sep-2019
https://dl.acm.org/doi/10.1007/s11042-019-7721-2
Naim AAaroud ASaadani S(2018)Automatic approach for the extraction of indexes of electric meters and waterProceedings of the 7th International Conference on Software Engineering and New Technologies10.1145/3330089.3330105(1-5)Online publication date: 26-Dec-2018
https://dl.acm.org/doi/10.1145/3330089.3330105
Zhu AGao RUchida S(2016)Could scene context be beneficial for scene text detection?Pattern Recognition10.1016/j.patcog.2016.04.01158:C(204-215)Online publication date: 1-Oct-2016
https://dl.acm.org/doi/10.1016/j.patcog.2016.04.011

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