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Adaptive Image Binarization Based on Multi-layered Stack of Regions

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Computer Analysis of Images and Patterns (CAIP 2019)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 11679))

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Abstract

The main purpose of conducted research is the development of a new image thresholding method, which is faster than typical adaptive methods and more accurate than global binarization. Since natural images captured by cameras are usually unevenly illuminated, due to unknown and various lighting conditions, an appropriate binarization influences the results of further image analysis significantly.

In this paper, the analysis of multi-layered stack of regions, being the enhancement of the single-layer version, is proposed to calculate the local image properties. Since the balance between the global and local adaptive thresholding requires the choice of an appropriate number of shifted layers and block size, its verification has been made using a database of test images. The proposed local threshold value is chosen as the mean local intensity corrected using two additional parameters subjected to optimization.

The developed procedure allows for more accurate and faster binarization, which can be applied in many technical systems. It has been verified by the example of text recognition accuracy for the non-uniformly illuminated document images in comparison to alternative global and local methods of similar of lower computational complexity.

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Authors and Affiliations

  1. Department of Signal Processing and Multimedia Engineering, Faculty of Electrical Engineering, West Pomeranian University of Technology, Szczecin, 26 Kwietnia 10, 71-126, Szczecin, Poland

    Hubert Michalak & Krzysztof Okarma

Authors
  1. Hubert Michalak
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  2. Krzysztof Okarma
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Correspondence to Krzysztof Okarma .

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Editors and Affiliations

  1. Department of Computer and Electrical Engineering and Applied Mathematics, University of Salerno, Fisciano (SA), Italy

    Mario Vento

  2. Department of Computer and Electrical Engineering and Applied Mathematics, University of Salerno, Fisciano (SA), Italy

    Gennaro Percannella

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Michalak, H., Okarma, K. (2019). Adaptive Image Binarization Based on Multi-layered Stack of Regions. In: Vento, M., Percannella, G. (eds) Computer Analysis of Images and Patterns. CAIP 2019. Lecture Notes in Computer Science(), vol 11679. Springer, Cham. https://doi.org/10.1007/978-3-030-29891-3_25

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  • DOI: https://doi.org/10.1007/978-3-030-29891-3_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-29890-6

  • Online ISBN: 978-3-030-29891-3

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