Share Email Print

Proceedings Paper

Scan image compression-encryption hardware system
Author(s): Nikolaos G. Bourbakis; R. Brause; C. Alexopoulos
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

This paper deals with the hardware design of an image compression/encryption scheme called SCAN. The scheme is based on the principles and ideas reflected by the specification of the SCAN language. SCAN is a fractal based context-free language which accesses sequentially the data of a 2D array, by describing and generating a wide range (near (nxn)) of space filling curves (or SCAN patterns) from a short set of simple ones. The SCAN method uses the algorithmic description of each 2D image as SCAN patterns combinations for the compression and encryption of the image data. Note that each SCAN letter or word accesses the image data with a different order (or sequence), thus the application of a variety of SCAN words associated with the compression scheme will produce various compressed versions of the same image. The compressed versions are compared in memory size and the best of them with the smallest size in bits could be used for the image compression/encryption. Note that the encryption of the image data is a result of the great number of possible space filling curves which could be generated by SCAN. Since the software implementation of the SCAN compression/encryption scheme requires some time, the hardware design and implementation of the SCAN scheme is necessary in order to reduce the image compression/encryption time to the real-time one. The development of such an image compression encryption system will have a significant impact on the transmission and storage of images. It will be applicable in multimedia and transmission of images through communication lines.

Paper Details

Date Published: 17 April 1995
PDF: 10 pages
Proc. SPIE 2419, Digital Video Compression: Algorithms and Technologies 1995, (17 April 1995); doi: 10.1117/12.206378
Show Author Affiliations
Nikolaos G. Bourbakis, SUNY/Binghamton (USA) and Univ. of Crete (Greece)
R. Brause, Geothe Univ. (Germany)
C. Alexopoulos, Univ. of Patras (Greece)

Published in SPIE Proceedings Vol. 2419:
Digital Video Compression: Algorithms and Technologies 1995
Arturo A. Rodriguez; Robert J. Safranek; Edward J. Delp, Editor(s)

© SPIE. Terms of Use
Back to Top