Comparing Hilditch, Rosenfeld, Zhang-Suen,and Nagendraprasad -Wang-Gupta Thinning

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Zhang-Suen,and Nagendraprasad -Wang-Gupta Thinning</title> <meta name="description" content="Comparing Hilditch, Rosenfeld, Zhang-Suen,and Nagendraprasad -Wang-Gupta Thinning"> <meta name="keywords" content="Hilditch algorithm, Nagendraprasad-Wang-Guptaalgorithm, Rosenfeld algorithm, Thinning, Zhang-suen algorithm"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <meta name="citation_title" content="Comparing Hilditch, Rosenfeld, Zhang-Suen,and Nagendraprasad -Wang-Gupta Thinning"> <meta name="citation_author" content="Anastasia Rita Widiarti"> <meta name="citation_publication_date" content="2011/06/28"> <meta name="citation_journal_title" content="International Journal of Computer and Information Engineering"> <meta name="citation_volume" content="5"> <meta name="citation_issue" content="6"> <meta name="citation_firstpage" content="563"> <meta name="citation_lastpage" content="567"> <meta 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Hilditch, Rosenfeld, Zhang- Suen, dan Nagendraprasad Wang Gupta (NWG) thinning algorithms for Javanese character image recognition. Thinning is an effective process when the focus in not on the size of the pattern, but rather on the relative position of the strokes in the pattern. The research analyzes the thinning of 60 Javanese characters. Time-wise, Zhang-Suen algorithm gives the best results with the average process time being 0.00455188 seconds. But if we look at the percentage of pixels that meet one-pixel thickness, Rosenfelt algorithm gives the best results, with a 99.98% success rate. From the number of pixels that are erased, NWG algorithm gives the best results with the average number of pixels erased being 84.12%. It can be concluded that the Hilditch algorithm performs least successfully compared to the other three algorithms. <iframe src="https://publications.waset.org/6492.pdf" style="width:100%; height:400px;" frameborder="0"></iframe> <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/search?q=Hilditch%20algorithm" title="Hilditch algorithm">Hilditch algorithm</a>, <a href="https://publications.waset.org/search?q=Nagendraprasad-Wang-Guptaalgorithm" title=" Nagendraprasad-Wang-Guptaalgorithm"> Nagendraprasad-Wang-Guptaalgorithm</a>, <a href="https://publications.waset.org/search?q=Rosenfeld%20algorithm" title=" Rosenfeld algorithm"> Rosenfeld algorithm</a>, <a href="https://publications.waset.org/search?q=Thinning" title=" Thinning"> Thinning</a>, <a href="https://publications.waset.org/search?q=Zhang-suen%20algorithm" title=" Zhang-suen algorithm"> Zhang-suen algorithm</a> </p> <p class="card-text"><strong>Digital Object Identifier (DOI):</strong> <a href="https://doi.org/10.5281/zenodo.1063020" target="_blank">doi.org/10.5281/zenodo.1063020</a> </p> <a href="https://publications.waset.org/6492/comparing-hilditch-rosenfeld-zhang-suenand-nagendraprasad-wang-gupta-thinning" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/6492/apa" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">APA</a> <a href="https://publications.waset.org/6492/bibtex" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">BibTeX</a> <a href="https://publications.waset.org/6492/chicago" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Chicago</a> <a href="https://publications.waset.org/6492/endnote" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">EndNote</a> <a href="https://publications.waset.org/6492/harvard" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">Harvard</a> <a href="https://publications.waset.org/6492/json" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">JSON</a> <a href="https://publications.waset.org/6492/mla" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">MLA</a> <a href="https://publications.waset.org/6492/ris" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">RIS</a> <a href="https://publications.waset.org/6492/xml" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">XML</a> <a href="https://publications.waset.org/6492/iso690" target="_blank" rel="nofollow" class="btn btn-primary btn-sm">ISO 690</a> <a href="https://publications.waset.org/6492.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">3919</span> </span> <p class="card-text"><strong>References:</strong></p> <br>[1] Srihari, S.N., Lam, S.W., Govindaraju, V., Srihari, R.K., and Hull, J.J. Document Image Understanding. New York: CEDAR, 1986. <br>[2] O-Gorman, L., and Kasturi, R. Executive briefing: documen image analysis. USA: IEEE Computer Society Press, 1997. <br>[3] M. Shimizu, H. Fukuda, and G. Nakamura. "Thinning Algorithm for Digital Figures of Characters", Proceeding 4th IEEE Southwest Symposium on Image Analysis and Interpretation, 2000.Pp: 83-87. <br>[4] Zhang, T. Y. and Suen, Ching Y., "A Fast Parallel Algorithms For Thinning Digital Patterns", Communication of the ACM, Vol 27, No. 3, Maret 1984, pp.236-239. <br>[5] Lam, L. and Suen, Ching Y., "An Evaluation Of Parallel Thinning Algorithms For Character Recognition", IEEE Transaction On Pattern Analysis And Machine Intelligence, Vol 17, No. 9, September 1995, pp.914-919. <br>[6] E. Adeline, Enhancement of Parallel Thinning Algorithm for Handwritten Characters Using Neural Network, Master Thesis, Department of Computer Science, Faculty of Computer Science and Information Technology, Universiti Technologi Malaysia, 2005. http://eprints.utm.my/3796/1/AdelineEngkamatMCD205ttt.pdf. <br>[7] Klette, Gisela. Skeletons in Digital Image Processing. 2002 <br>[8] K.H. Lee, K.B. Eom, and R.L. Kashyap "Character Recognition Based on Attribute-Dependent Programmed Grammar", IEEE Transaction On Pattern Analysis And Machine Intelligence, VoL. 14, No. 11, November 1992, pp.1122-1128. <br>[9] Nagendraprasad, MV., Wang, PSP., and Gupta, A., "Algorithms for Thinning and Rethickening Binary Digital Pattern", Digital Signal Processing, Vol. 3, 1993, pp. 97-102. http://dspace.mit.edu/ bitstream/handle/1721.1/46843/algorithmsforthi00nage.pdf?sequence=1 <br>[10] Zhang, T. Y. dan Wang, P. S. P., "Analysis of Thinning Algorithms", College of Computer Science Northeastern University Boston, MA 02115. 1992, pp.763-766. <br>[11] L. Lam, SW Lee, and CY. Suen, "Thinning Methodologies - A Comprehensive Survey", IEEE Transaction on Pattern Analysis and Machine Intelligence. Vol. 14, No. 9, September 1992, pp. 869-885. <br>[12] Dawoud, Amer dan Kamel, Mohamed, "New Approach for the Skeletonization of Handwritten Characters in Gray-Level Images", Proceedings of the Seventh International Conference on Document Analysis and Recognition (ICDAR 2003), IEEE. <br>[13] Jang, BK., and Chin, RT., -Analysis of Thinning Algorithms Using Mathematical Morphology", IEEE Transactions on Pattern Analysis and Machine Intellegence. Vol. 12, No. 6, 1990, pp. 541-551. <br>[14] Rinaldi, Munir. Pengolahan Citra Digital dengan Pendekatan Algoritmik. Bandung: Penerbit Informatika, 2004. <br>[15] Taussaint, Godfried. Skeletons. http://www.citr.auckland.ac.nz/ <br>[16] Wang, PSP., and Zhang, YY. "A Fast and Flexsible Thinning Algorithm", IEEE Transactions on Computer. 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Comparing Hilditch, Rosenfeld, Zhang-Suen,and Nagendraprasad -Wang-Gupta Thinning