Segmentation algorithm via Cellular Neural/Nonlinear Network: implementation on Bio-inspired hardware platform


Creative Commons License

Karabiber F., VECCHIO P., GRASSI G.

EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING, 2011 (SCI-Expanded) identifier

Özet

The Bio-inspired (Bi-i) Cellular Vision System is a computing platform consisting of sensing, array sensing-processing, and digital signal processing. The platform is based on the Cellular Neural/Nonlinear Network (CNN) paradigm. This article presents the implementation of a novel CNN-based segmentation algorithm onto the Bi-i system. Each part of the algorithm, along with the corresponding implementation on the hardware platform, is carefully described through the article. The experimental results, carried out for Foreman and Car-phone video sequences, highlight the feasibility of the approach, which provides a frame rate of about 26 frames/s. Comparisons with existing CNN-based methods show that the conceived approach is more accurate, thus representing a good trade-off between real-time requirements and accuracy.