1. Implementation of a cellular neural network–based segmentation algorithm on the bio-inspired vision system.
- Author
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Fethullah Karabiber, Giuseppe Grassi, Pietro Vecchio, Sabri Arik, and M. Erhan Yalcin
- Subjects
- *
ARTIFICIAL neural networks , *ALGORITHMS , *BIOSENSORS , *IMAGE processing , *COMPARATIVE studies , *FEASIBILITY studies - 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 framesec. 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. [ABSTRACT FROM AUTHOR]
- Published
- 2011