An analogic CNN algorithm is proposed for detection of multiple moving objects in high resolution, grey-scale images taken from a fixed camera. The algorithm, based on simple 3 x 3 templates, can be implemented using CNN hardware, providing the real-time operation required in surveillance and traffic control applications. Efficient separation of moving objects from the background is obtained through automatic threshold selection. The performance of the proposed method is shown using real-life indoor and outdoor video sequences. Copyright (C) 2004 John Wiley Sons, Ltd.

Costantini, G., Casali, D., Perfetti, R. (2004). Analogic CNN algorithm for estimating position and size of moving objects. INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS, 32(6), 509-522 [10.1002/cta.293].

Analogic CNN algorithm for estimating position and size of moving objects

COSTANTINI, GIOVANNI;
2004-01-01

Abstract

An analogic CNN algorithm is proposed for detection of multiple moving objects in high resolution, grey-scale images taken from a fixed camera. The algorithm, based on simple 3 x 3 templates, can be implemented using CNN hardware, providing the real-time operation required in surveillance and traffic control applications. Efficient separation of moving objects from the background is obtained through automatic threshold selection. The performance of the proposed method is shown using real-life indoor and outdoor video sequences. Copyright (C) 2004 John Wiley Sons, Ltd.
2004
Pubblicato
Rilevanza internazionale
Articolo
Sì, ma tipo non specificato
Settore ING-IND/31 - ELETTROTECNICA
English
Cellular neural networks; Image processing; Moving object detection
Costantini, G., Casali, D., Perfetti, R. (2004). Analogic CNN algorithm for estimating position and size of moving objects. INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS, 32(6), 509-522 [10.1002/cta.293].
Costantini, G; Casali, D; Perfetti, R
Articolo su rivista
File in questo prodotto:
File Dimensione Formato  
2004-Analogic CNN algorithm.pdf

accesso aperto

Licenza: Non specificato
Dimensione 250.65 kB
Formato Adobe PDF
250.65 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/30007
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? 3
social impact