Implementation of a cellular neural network-based segmentation algorithm on the bio-inspired vision system
Tarih
2011Yazar
Arik, Sabri
Karabiber, Fethullah
GRASSI, Giuseppe
VECCHIO, Pietro
Yalçın, Müştak Erhan
Üst veri
Tüm öğe kaydını gösterÖzet
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. (C) 2011 SPIE and IS&T. [DOI: 10.1117/1.3533327]
Koleksiyonlar
- Makale [92796]