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

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

2 Scopus Citations
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Author(s)

  • Han Huang
  • Zhi-Kai Huang
  • Yong-Li Ma
  • Ling-Ying Hou

Detail(s)

Original languageEnglish
Title of host publicationIntelligent Computing Theories and Application
Subtitle of host publication14th International Conference, ICIC 2018, Proceedings
EditorsDe-Shuang Huang, Vitoantonio Bevilacqu, Prashan Premaratne, Phalguni Gupta
PublisherSpringer, Cham
Pages15-24
Volume1
ISBN (electronic)978-3-319-95930-6
ISBN (print)978-3-319-95929-0
Publication statusPublished - Aug 2018

Publication series

NameLecture Notes in Computer Science (including subseries Information Systems and Applications, incl. Internet/Web, and HCI)
PublisherSpringer, Cham
VolumeLNCS 10954
ISSN (Print)0302-9743
ISSN (electronic)1611-3349

Conference

Title14th International Conference on Intelligent Computing, ICIC 2018
PlaceChina
CityWuhan
Period15 - 18 August 2018

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 In order to preserve strokes of a Chinese character while enhancing character details for degraded historical document image, we propose an adaptive segmentation algorithm for degraded historical document image binarization based on background estimation for non-uniform illumination images.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.

Research Area(s)

  • Background estimation, Blind/referenceless image spatial quality evaluator, Mathematical morphology, Top-hat transform

Citation Format(s)

An Adaptive Segmentation Algorithm for Degraded Chinese Rubbing Image Binarization Based on Background Estimation. / Huang, Han; Huang, Zhi-Kai; Ma, Yong-Li et al.
Intelligent Computing Theories and Application: 14th International Conference, ICIC 2018, Proceedings. ed. / De-Shuang Huang; Vitoantonio Bevilacqu; Prashan Premaratne; Phalguni Gupta. Vol. 1 Springer, Cham, 2018. p. 15-24 (Lecture Notes in Computer Science (including subseries Information Systems and Applications, incl. Internet/Web, and HCI); Vol. LNCS 10954).

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review