Arabic Textual Images Compression Approach | Zendy

Jassem Mtimet | Zendy; Hamid Amiri | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Arabic Textual Images Compression Approach

Author(s) -

Jassem Mtimet,

Hamid Amiri

Publication year - 2014

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2014.08.091

Subject(s) - computer science , encode , arabic , coding (social sciences) , data compression , compression (physics) , artificial intelligence , image compression , compression ratio , pattern recognition (psychology) , image (mathematics) , natural language processing , image processing , philosophy , biochemistry , chemistry , linguistics , statistics , mathematics , materials science , internal combustion engine , automotive engineering , engineering , composite material , gene

In this paper, a novel compression approach for large Arabic textual images is proposed. Initially, input texts are segmented into patterns which represent sub-words. Then, patterns-matching procedure is used in order to find similar patterns within the image. Finally, to optimize the performances of this approach, an adaptive arithmetic coding is used to encode the resulting data streams. Experimental results show that the average compression ratio of our approach is better than other existing algorithms

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research