1 January 2011 Implementation of a cellular neural network-based segmentation algorithm on the bio-inspired vision system
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Abstract
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.
© (2011) Society of Photo-Optical Instrumentation Engineers (SPIE)
Fethullah Karabiber, Giuseppe Grassi, Pietro Vecchio, Sabri Arik, M. Erhan Yalcin, "Implementation of a cellular neural network-based segmentation algorithm on the bio-inspired vision system," Journal of Electronic Imaging 20(1), 013004 (1 January 2011). https://doi.org/10.1117/1.3533327 . Submission:
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