Title :
Early segmentation in video compression using CNN processors
Author :
László, K. ; Ziliani, F. ; Roska, Tamas ; Kunt, M.
Author_Institution :
Comput. & Autom. Inst., Hungarian Acad. of Sci., Budapest, Hungary
Abstract :
Two analogic (analog and logic) CNN algorithms are presented which segment a video sequence into objects. The algorithms are mainly based on 3 by 3, linear templates. This allows the CNN Universal Machine to execute the task achieving enormous computation speed (1012 equivalent operation per second). The proposed segmentation algorithms rely on texture and contour information only. They differ in the use or not of the color information. The estimated execution time proves that the proposed segmentation method may be implemented in real time. This result and the quality of the obtained frame description are very appealing in the context of the new video coding standard MPEG-4
Keywords :
cellular neural nets; data compression; image colour analysis; image segmentation; image texture; video coding; CNN Universal Machine; CNN processors; MPEG-4; analogic CNN algorithms; color information; contour information; early segmentation; texture; video coding standard; video compression; video sequence; Analog computers; Cellular neural networks; Image color analysis; Image segmentation; Laboratories; Layout; MPEG 4 Standard; Signal processing algorithms; Turing machines; Video compression;
Conference_Titel :
Cellular Neural Networks and Their Applications Proceedings, 1998 Fifth IEEE International Workshop on
Conference_Location :
London
Print_ISBN :
0-7803-4867-2
DOI :
10.1109/CNNA.1998.685359