DocumentCode :
2286262
Title :
Object-oriented image analysis via analogic CNN algorithms. II. Image synthesis and consistency observation
Author :
Grassi, Giuseppe ; Grieco, Luigi Alfredo
Author_Institution :
Dipt. di Ingegneria dell´´Innovazione, Lecce Univ., Italy
fYear :
2002
fDate :
22-24 Jul 2002
Firstpage :
180
Lastpage :
187
Abstract :
For pt.I see ibid., p.172-9 (2002). In the context of image analysis for object-oriented coding schemes, this paper presents new analogic CNN algorithms for implementing the image synthesis and consistency observation stages. Along with the motion estimation algorithm illustrated in the companion paper, the proposed approach represents a framework for implementing CNN-based real-time image analysis. Simulation results, carried out for Miss America video sequence, confirm the validity of the algorithms developed herein.
Keywords :
cellular neural nets; image sequences; object recognition; real-time systems; video coding; analogic CNN algorithms; cellular neural network; image consistency observation; image synthesis; motion estimation; object recognition; object-oriented coding; object-oriented image analysis; real-time image analysis; simulation; video coding; video sequence; Cellular neural networks; Image analysis; Image coding; Image color analysis; Image generation; Image motion analysis; Image segmentation; Image sequence analysis; Motion estimation; Object oriented modeling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cellular Neural Networks and Their Applications, 2002. (CNNA 2002). Proceedings of the 2002 7th IEEE International Workshop on
Print_ISBN :
981-238-121-X
Type :
conf
DOI :
10.1109/CNNA.2002.1035051
Filename :
1035051
Link To Document :
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