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An Adaptive Segmentation Algorithm for Degraded Chinese Rubbing Image Binarization Based on Background Estimation

  • Han Huang
  • Zhi-Kai Huang
  • Yong-Li Ma
  • Ling-Ying Hou
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10954)

Abstract

Image Segmentation plays an important role in image processing and analysis. In order to preserve strokes of a Chinese character while enhancing character details for degraded historical document image, we propose an adaptive segmentation algorithm for degraded historical document image binarization based on background estimation for non-uniform illumination images. The novelty of the proposed method is that find an optimal background estimation based on Blind/Referenceless Image Spatial QUality Evaluator. The proposed method has four steps: (i) preprocess using median filtering; (ii) extraction of the red color components; (iii) a morphological operation in order to find an optimal background estimation; and (iv) segmented binary image using Otsu’s Thresholding. Experimental results demonstrate that it is capable of extracting more accurate segmentation of characters for degraded Chinese rubbing document image.

Keywords

Top-Hat transform Blind/Referenceless Image Spatial QUality Evaluator Background estimation Mathematical morphology 

Notes

Acknowledgement

This work was supported by the National Natural Science Foundation of China (Grant No. 61472173), Natural Science Foundation of Jiangxi Province of China, No. 20161BAB202042, the grants from the Educational Commission of Jiangxi province of China, No. GJJ151134.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Han Huang
    • 1
  • Zhi-Kai Huang
    • 2
  • Yong-Li Ma
    • 2
  • Ling-Ying Hou
    • 2
  1. 1.Department of Mechanical and Biomedical EngineeringCity University of Hong KongKowloon TongHong Kong
  2. 2.College of Mechanical and Electrical EngineeringNanchang Institute of TechnologyNanchangChina

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