A simple iterative thinning algorithm for text and shape binary images

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Thinning or skeletonization is become a curial step in many document image analysis and recognition application as a pre-process stage. These applications such as optical character recognition OCR, optical script recognition OSR, and optical font recognition OFR widely adopt many exist methods, some thinning challenging defect the performance of these applications. However, further enhancement for thinning technique is indeed. A simple iterative thinning algorithm is proposed for binary images domain. Thereafter, a benchmark dataset is designed for thinning algorithm evaluation is used. Finally, The evaluation experiments result are compared with some other major thinning methods to proof the proposed method efficiency. The proposed algorithm visual experiments shows outperform for many thinning challenges such as one pixel width, topology preserving, rotation tolerance, and tail occurrences.

Original languageEnglish
Pages (from-to)274-281
Number of pages8
JournalJournal of Theoretical and Applied Information Technology
Volume63
Issue number2
Publication statusPublished - 2014

Fingerprint

Binary images
Binary Image
Thinning
Optical character recognition
Image recognition
Image analysis
Pixels
Experiments
Topology
Defects
Skeletonization
Document Analysis
Image Recognition
Character Recognition
Evaluation
Text
Image Analysis
Experiment
Tolerance
Tail

Keywords

  • Iterative Thinning
  • OCR
  • OFR
  • OSR
  • Skeletonization
  • Thinning

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

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AB - Thinning or skeletonization is become a curial step in many document image analysis and recognition application as a pre-process stage. These applications such as optical character recognition OCR, optical script recognition OSR, and optical font recognition OFR widely adopt many exist methods, some thinning challenging defect the performance of these applications. However, further enhancement for thinning technique is indeed. A simple iterative thinning algorithm is proposed for binary images domain. Thereafter, a benchmark dataset is designed for thinning algorithm evaluation is used. Finally, The evaluation experiments result are compared with some other major thinning methods to proof the proposed method efficiency. The proposed algorithm visual experiments shows outperform for many thinning challenges such as one pixel width, topology preserving, rotation tolerance, and tail occurrences.

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