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research-article

Curved text detection in blurred/non-blurred video/scene images

Authors:

Palaiahnakote Shivakumara,

Umapada PalAuthors Info & Claims

Volume 78, Issue 18

Pages 25629 - 25653

https://doi.org/10.1007/s11042-019-7721-2

Published: 01 September 2019 Publication History

Abstract

Text detection in video/images is challenging due to the presence of multiple blur caused by defocus and motion. In this paper, we present a new method for detecting texts in blurred/non-blurred images. Unlike the existing methods that use deblurring or classifiers, the proposed method estimates degree of blur in images based on contrast variations in neighbor pixels and a low pass filter, which results in candidate pixels for deblurring. We consider gradient values of each pixel as the weight for the degree of blur. The proposed method then performs K-means clustering on weighted values of candidate pixels to get text candidates irrespective of blur types. Next, Bhattacharyya distance is used to extract symmetry property of texts to remove false text candidates, which provides text components. Further, the proposed method fixes bounding box for each text component based on the nearest neighbor criteria and direction of the text component. Experimental results on defocus, motion, non-blurred images and standard datasets of curved text show that the proposed method outperforms the existing methods.

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Cited By

Xue MHe YXie PHe ZFeng X(2023)LAE-GAN: a novel cloud-based Low-light Attention Enhancement Generative Adversarial Network for unpaired text imagesJournal of Cloud Computing: Advances, Systems and Applications10.1186/s13677-023-00533-412:1Online publication date: 23-Oct-2023
https://dl.acm.org/doi/10.1186/s13677-023-00533-4
Pandey DPandey BWairya S(2021)Hybrid deep neural network with adaptive galactic swarm optimization for text extraction from scene imagesSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-020-05245-425:2(1563-1580)Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1007/s00500-020-05245-4
Nandanwar LShivakumara PKumar ALu TPal ULopresti D(2020)A New Common Points Detection Method for Classification of 2D and 3D Texts in Video/Scene ImagesDocument Analysis Systems10.1007/978-3-030-57058-3_36(512-528)Online publication date: 26-Jul-2020
https://dl.acm.org/doi/10.1007/978-3-030-57058-3_36

Index Terms

Curved text detection in blurred/non-blurred video/scene images
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Video segmentation
      2. Computer vision tasks

Index terms have been assigned to the content through auto-classification.

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Information & Contributors

Information

Published In

cover image Multimedia Tools and Applications

Multimedia Tools and Applications Volume 78, Issue 18

Sep 2019

1576 pages

ISSN:1380-7501

Issue’s Table of Contents

Copyright © 2019 Springer Science+Business Media, LLC, part of Springer Nature.

Publisher

Kluwer Academic Publishers

United States

Publication History

Published: 01 September 2019

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Citations

Cited By

Xue MHe YXie PHe ZFeng X(2023)LAE-GAN: a novel cloud-based Low-light Attention Enhancement Generative Adversarial Network for unpaired text imagesJournal of Cloud Computing: Advances, Systems and Applications10.1186/s13677-023-00533-412:1Online publication date: 23-Oct-2023
https://dl.acm.org/doi/10.1186/s13677-023-00533-4
Pandey DPandey BWairya S(2021)Hybrid deep neural network with adaptive galactic swarm optimization for text extraction from scene imagesSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-020-05245-425:2(1563-1580)Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1007/s00500-020-05245-4
Nandanwar LShivakumara PKumar ALu TPal ULopresti D(2020)A New Common Points Detection Method for Classification of 2D and 3D Texts in Video/Scene ImagesDocument Analysis Systems10.1007/978-3-030-57058-3_36(512-528)Online publication date: 26-Jul-2020
https://dl.acm.org/doi/10.1007/978-3-030-57058-3_36
Mittal AShivakumara PPal ULu TBlumenstein MLopresti D(2020)A New Context-Based Method for Restoring Occluded Text in Natural Scene ImagesDocument Analysis Systems10.1007/978-3-030-57058-3_33(466-480)Online publication date: 26-Jul-2020
https://dl.acm.org/doi/10.1007/978-3-030-57058-3_33

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