WFA Image Encoding with New Partitioning Method
Main Article Content
Abstract
Weight Finite Automata (WFA) image encoding is a method for encoding images which has been brought up by Culik and Kari [1]. They suggest the way to encode a digital image by applying quadtree partition to divide an image into subsquares and then construct subdividing images with linear combination as a weighted automaton. Nonatree is a new way to partition an image into a nine subsqaure-tree. Instead of quadtree partition which is used by Culik and Kari, nonatree partition is applied with WFA to encode digital images.
Keywords: WFA, partition image, compression
Corresponding author: E-mail: thommarat_tum@yahoo.com , kpkorako@kmitl.ac.th
Article Details
Copyright Agreement Statement
The corresponding author has to submit Copyright Agreement form after the article is accepted for publication in order to warrant that this contribution is original and that he/she has full power to make this grant. The author signs for and accepts responsibility for releasing this material on behalf of any and all co-authors.
The author(s) grant Current Applied Science and Technology a non-exclusive, irrevocable, royalty-free license to publish, reproduce, distribute, and archive the article in print and electronic form with effect if and when the article is accepted for publication. In the event that the article is withdrawn prior to acceptance or is declined, this agreement shall have no effect, and no party shall be bound by it.
The author(s) retain copyright of this article, including but not limited to the right to reproduce and distribute the article, to include it in a thesis or book, and to post it on an institutional or personal repository, provided that the original publication in Current Applied Science and Technology is properly cited.
References
[2] Culik K. II and Kari J., 1995, Finite state met-hods for compression and manipulation of images, Data Compression Conference. DCC’95. Proceedings, 28-30 March 1995, Pages: 142-151.
[3] Culik K. II and Kari J.., 1995, Inferecce Algor-ithm for WFA and Image Compression, Fractal Image Compression, Thoery and Application, Fisher editor, Pages : 243-258, Springer-Verlag New York, Inc.
[4] U. Hafner, 1996, Refining image Compression with weighted finite automata, Data Co-mpression Conference. DCC’96. Procee-dings, 31 March-3 April 1996, Pages: 359-368.
[5] Culik K. II and Kari J. and Valenta V., 1997, Compres-sion of silhouette-like images based on WFA, Data Compression Conference. DCC’97. Proceedings, 25-27 March 1997 Pages: 433.
[6] Z. Jiang and Litow B. and de Vel O., 2001, An inference implementation based on exten-ded weighted finite automata [for image compression], Computer Science Confe-rence. ACSC 2001. Proceedings. 24th Australasian, 29 Jan-4Feb 2001, Pages: 100-108.
[7] Y. sivasubramanyam and Kamala Krithivasan, 2001, Image Representation using distributed Weighted Finite Automata, Published by Elsevier Science B.V..
[8] Yih-Kai lin and Hsu-Chun Yen, 2003, “An ω-Automata Approach to the Representation of Bilevel Images”, IEEE.
[9] Culik K. II and Peter von Rosenberg C., Generalized Weighted Finite automata Based Image Compression, Department of Computer Science University of South Carolina Columbia, S.C. 29208, U.S.A.
[10] Culik K., Valenta, V., 1996, Finite automata based compression of bi-level images, Data Compression Conference, 1996. DCC’ 96. Proceedings, 31 March-3 April 1996 Pages: 280-289.
[11] Culik K. II and Kari J., Finite State Transformations of Image, Department of Computer Science University of South Carolina Columbia, S.C. 29208, U.S.A.
[12] Katritzke, Techiques for WFA Construction, Pages: 36-58.