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Implementation of a cellular neural network–based segmentation algorithm on the bio-inspired vision system

[+] Author Affiliations
Fethullah Karabiber

Istanbul University, Department of Computer Engineering, 34320 Istanbul, Turkey

Giuseppe Grassi

Università del Salento, Dipartimento di Ingegneria dell’Innovazione, 73100 Lecce, Italy

Pietro Vecchio

Università del Salento, Dipartimento di Ingegneria dell’Innovazione, 73100 Lecce, Italy

Sabri Arik

Istanbul University, Department of Computer Engineering, 34320 Istanbul, Turkey

M. Erhan Yalcin

Istanbul Technical University, Department of Electronics and Communication Engineering, 34469, Maslak, Istanbul, Turkey

J. Electron. Imaging. 20(1), 013004 (March 09, 2011). doi:10.1117/1.3533327
History: Received November 04, 2009; Revised October 18, 2010; Accepted December 06, 2010; Published March 09, 2011; Online March 09, 2011
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Based on the cellular neural network (CNN) paradigm, the bio-inspired (bi-i) cellular vision system is a computing platform consisting of state-of-the-art sensing, cellular sensing-processing and digital signal processing. This paper presents the implementation of a novel CNN-based segmentation algorithm onto the bi-i system. The experimental results, carried out for different benchmark video sequences, highlight the feasibility of the approach, which provides a frame rate of about 26 frame/sec. Comparisons with existing CNN-based methods show that, even though these methods are from two to six times faster than the proposed one, the conceived approach is more accurate and, consequently, represents a satisfying trade-off between real-time requirements and accuracy.

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© 2011 SPIE and IS&T

Citation

Fethullah Karabiber ; Giuseppe Grassi ; Pietro Vecchio ; Sabri Arik and M. Erhan Yalcin
"Implementation of a cellular neural network–based segmentation algorithm on the bio-inspired vision system", J. Electron. Imaging. 20(1), 013004 (March 09, 2011). ; http://dx.doi.org/10.1117/1.3533327


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