Dergiler / Istanbul University Journal of Electrical and Electronics Engineering / 2011 / Cilt: 11 - Sayı: 2

Hybrid lossless compression method for binary images

Sayfa
1399–1405
Yayın Tarihi
2022-10-18
DOI
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Computed mathematical results related to compression performance are represented comparatively in a tabular format.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:In this paper, we propose a lossless compression scheme for binary images which consists of a novel encoding algorithm which uses a new edge tracking algorithm.
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Temel Bulgular & Veri:Experimental results show that using the proposed encoding method together with any traditional compressing method improves the compression performance.
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Sonuç & Katkı:Computed mathematical results related to compression performance are represented comparatively in a tabular format.
🔬Tür:Araştırma Makalesi
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Alan Parametreleri

Abstract

In this paper, we propose a lossless compression scheme for binary images which consists of a novel encoding algorithm which uses a new edge tracking algorithm. The proposed compression scheme has two sub-stages: (i) encoding binary image data using the proposed encoding method (ii) compression the encoded image data using any well-known image compression method such as Huffman, Run-Length or Lempel- Ziv-Welch (LZW). The proposed encoding method contains two subsequent processes: (i) determining the starting points of independent objects (ii) obtaining their edge points and geometrical shapes information. Experimental results show that using the proposed encoding method together with any traditional compressing method improves the compression performance. Computed mathematical results related to compression performance are represented comparatively in a tabular format.

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Bu Makaleye Atıf Yap

TALU, M. F., TÜRKOĞLU, İ. (2022). Hybrid lossless compression method for binary images. Istanbul University Journal of Electrical and Electronics Engineering, Cilt: 11 - Sayı: 2, 1399–1405. https://ajindex.com/articles/543687

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Kaynakça (13)

  1. Russ, J.C.: ‘The Image Processing Handbook’, North Carolina State University, pp.35-41, 2002
  2. Pitas, I.: ‘Digital Image Processing Algorithms and Applications’, United States of America, pp.242-244, 2000
  3. Nelson M, Gailly JL. “Data Compression Book”, Second edition. New York: M&T Books, 1996
  4. Shi, Yun Q., and Sun, H., “Image and video compression for multimedia engineering”, ISBN 0-8493-3491-8, Chapter 6, pp.20-23, 2000
  5. Abdat, M., and Bellanger, M.G., “Combin- ing Gray coding and JBIG for lossless image compression,” Proc. ICIP-94, vol.3 pp.851- 855, 1999
  6. Culik, K. and Valenta, V., “Finite automata based compression of bi-level images,” Proc. Data Compression, pp.280-289, 1996
  7. Phimoltares, S., Chamnongthai, K., and Lur- sinsap, C., “Hybrid Binary Image Compres- sion”, Fifth International Symposium on Signal Processing and its Applications, ISSPA ’99, Brisbane, Australia, 1999
  8. Tompkins, D., and Kossentini, F., “A Fast Segmentation Algorithm for Bi-Level Image Compression using JBIG2”, 0-7803-5467-2/99, IEEE, 1999
  9. Bogdan J. F., “Lossless binary image com- pression using logic functions and spectra”, Computers and Electrical Engineering 30, pp.17–43, 2004
  10. CCITT Standard Fax Images at http://www. cs.waikato.ac.nz/~singlis/ccitt.html
  11. Turkoglu, I. and Arslan, A., “An Edge Trac- ing Method Developed For Object Recogni- tion”, The 7-th International Conference in Central Europe on Computer Graphics, pp. 9-12, Plzen, Slovakia (1999
  12. Talu, M.F., Tatar, Y., “A new edge tracing method developed for object recognition”, TAINN 2003, Çanakkale, Haziran 2003
  13. Akimov, A., Kolesnikov, A. and Franti, P., «Lossless compression of map contours by context tree modeling of chain codes», Pattern Recognition, 40 (3), 944-952, March 2007.