Title :
An object-oriented approach to video coding via the CNN Universal Machine
Author :
Toffels, A. ; Roska, Tamáis ; Chua, Leon O.
Author_Institution :
Inst. of Power Syst. & Power Econ., Tech. Hochschule Aachen, Germany
Abstract :
The cellular neural network Universal Machine (CNNUM) is applied to object-oriented image compression algorithms and proves its universality as a hardware platform for future applications. The estimated processing times allow a real-time analysis of the video sequence and outdo the performance of other comparable digital devices reported
Keywords :
cellular neural nets; computer vision; data compression; image segmentation; image sequences; object-oriented methods; video coding; CNN Universal Machine; CNNUM; cellular neural network; image compression; object labelling; object-oriented method; processing times; real-time analysis; segmentation; universality; video coding; video sequence; Cellular neural networks; Image coding; Image segmentation; Labeling; Power engineering computing; Power system economics; Turing machines; Video coding; Video compression; Video sequences;
Conference_Titel :
Cellular Neural Networks and their Applications, 1996. CNNA-96. Proceedings., 1996 Fourth IEEE International Workshop on
Conference_Location :
Seville
Print_ISBN :
0-7803-3261-X
DOI :
10.1109/CNNA.1996.566481
