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