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Machine Vision and Applications
Erschienen in: Machine Vision and Applications 7/2017

07.04.2017 | Special Issue Paper

Robust and parallel Uyghur text localization in complex background images

verfasst von: Yun Song, Jianjun Chen, Hongtao Xie, Zhineng Chen, Xingyu Gao, Xi Chen

Erschienen in: Machine Vision and Applications | Ausgabe 7/2017

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Abstract

Uyghur text localization in complex background images is a significant research for Uyghur image content analysis. In this paper, we propose a robust Uyghur text localization method in complex background images and provide a CPU–GPU heterogeneous parallelization scheme. Firstly, a multi-color-channel enhanced maximally stable extremal region is used to extract components in images, which is robust to blur and low contrast. Secondly, a two-stage component classification system is used to filter out non-text components. Finally, a component connected graph algorithm is proposed to construct text lines. Experiments on the proposed dataset demonstrate that our algorithm compares favorably with the state-of-the-art algorithms when handling Uyghur texts. Besides, the heterogeneous parallel implementation achieves 12.5 times speedup.
Vorheriger Artikel Decay-weighted extreme learning machine for balance and optimization learning
Nächster Artikel Triple-Bit Quantization with Asymmetric Distance for Image Content Security

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Metadaten
Titel
Robust and parallel Uyghur text localization in complex background images
verfasst von
Yun Song
Jianjun Chen
Hongtao Xie
Zhineng Chen
Xingyu Gao
Xi Chen
Publikationsdatum
07.04.2017
Verlag
Springer Berlin Heidelberg
Erschienen in
Machine Vision and Applications / Ausgabe 7/2017
Print ISSN: 0932-8092
Elektronische ISSN: 1432-1769
DOI
https://doi.org/10.1007/s00138-017-0837-3

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