Regular Articles

Binary document image compression using a three-symbol grouped code dictionary

[+] Author Affiliations
Hermilo Sánchez-Cruz

Universidad Autónoma de Aguascalientes , Centro de Ciencias Básicas, Departamento de Ciencias de la Computación, Av. Universidad 940, Col. Cd Universitaria, CP. 20131, Aguascalientes, Aguascalientes, México

Mario A. Rodríguez-Díaz

Universidad Autónoma de Aguascalientes , Centro de Ciencias Básicas, Departamento de Ciencias de la Computación, Av. Universidad 940, Col. Cd Universitaria, CP. 20131, Aguascalientes, Aguascalientes, México

J. Electron. Imaging. 21(2), 023013 (May 21, 2012). doi:10.1117/1.JEI.21.2.023013
History: Received August 11, 2011; Revised February 10, 2012; Accepted February 28, 2012
Text Size: A A A

Abstract.  A novel method of lossy compression for images of text documents is proposed. The method is based on classifying the objects, characters, and pictures that appear in the images. We used the Tanimoto distance to group the objects into different classes to create an object dictionary; then, we codified the instances of each class by means of a code of three symbols called the three orthogonal symbol chain code (3OT). We applied an entropy coder to the resulting chain, which groups the symbols of 3OT; finally, we compressed the chain obtained by using the Paq8l archiver, which is based on a context-mixing algorithm divided into a predictor and an arithmetic coder. We obtained a high performance in memory storage, with an average of 2.17 times better compression levels with respect to the international standard Joint Bi-level Image Experts Group 2 on its lossy information version.

Figures in this Article
© 2012 SPIE and IS&T

Citation

Hermilo Sánchez-Cruz and Mario A. Rodríguez-Díaz
"Binary document image compression using a three-symbol grouped code dictionary", J. Electron. Imaging. 21(2), 023013 (May 21, 2012). ; http://dx.doi.org/10.1117/1.JEI.21.2.023013


Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Advertisement
  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.