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. For pt.I see ibid., p.172-9 (2002)
Object-Oriented Image Analysis via Analogic CNN Algorithms - Part II: Image Synthesis and Consistency Observation / Grassi, G.; Grieco, Luigi Alfredo. - (2002), pp. 180-187. (Intervento presentato al convegno 7th IEEE International Workshop on Cellular Neural Networks and Their Applications, CNNA 2002 tenutosi a Frankfurt, Germany nel July 22-24, 2002) [10.1109/CNNA.2002.1035051].
Object-Oriented Image Analysis via Analogic CNN Algorithms - Part II: Image Synthesis and Consistency Observation
GRIECO, Luigi Alfredo
2002-01-01
Abstract
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. For pt.I see ibid., p.172-9 (2002)I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
