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Morphological Gradient Analysis and Contour Feature Learning for Locating Text in Natural Scene Images

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Computer Vision and Image Processing (CVIP 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1568))

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Abstract

We use text as the primary medium for providing precise information. Text could be major source of information for understanding of a scene imagery or video, once it is recognized. Although identifying and understanding textual information is fairly simple for us, it can be extremely complex task for machines. Variations such as color, orientation, scale, flow, lighting, noise, occlusion, language features and font can make this task of computer vision challenging. Detecting presence of text and precisely locating regions of text are vital for faster and precise recognition. Due to the complexity of the task, most of the popular techniques of today require an intense training phase and powerful computation infrastructure. In the proposed method, we have tried to minimize the amount of training required to achieve a decent text localization result. We have observed that, morphological gradient analysis enhances textual regions and contour feature analysis can help to eliminate non-textual components. Combination of these techniques produces promising results with small dataset, minimal training and limited computational ability. Also, the proposed detector can detect text across multiple languages and is fairly robust against the variations such as orientation and scale. The proposed method achieves an F-measure of 0.77 on MSRA-TD500 after the training with 300 images.

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Authors and Affiliations

  1. Department of Computer Science, Mangalore University, Mangalore, Karnataka, 574199, India

    B. H. Shekar

  2. Government First Grade College Uppinangady, Uppinangady, Karnataka, 574241, India

    S. Raveeshwara

Authors
  1. B. H. Shekar
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  2. S. Raveeshwara
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Corresponding author

Correspondence to S. Raveeshwara .

Editor information

Editors and Affiliations

  1. Indian Institute of Technology Roorkee, Roorkee, India

    Balasubramanian Raman

  2. Indian Institute of Technology Ropar, Ropar, India

    Subrahmanyam Murala

  3. Jadavpur University, Kolkata, India

    Ananda Chowdhury

  4. Indian Institute of Technology Ropar, Ropar, India

    Abhinav Dhall

  5. Indian Institute of Technology Ropar, Ropar, India

    Puneet Goyal

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Shekar, B.H., Raveeshwara, S. (2022). Morphological Gradient Analysis and Contour Feature Learning for Locating Text in Natural Scene Images. In: Raman, B., Murala, S., Chowdhury, A., Dhall, A., Goyal, P. (eds) Computer Vision and Image Processing. CVIP 2021. Communications in Computer and Information Science, vol 1568. Springer, Cham. https://doi.org/10.1007/978-3-031-11349-9_22

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  • DOI: https://doi.org/10.1007/978-3-031-11349-9_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-11348-2

  • Online ISBN: 978-3-031-11349-9

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