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Segmentation Algorithm via Cellular Neural/Nonlinear Network: Implementation on Bio-Inspired Hardware Platform

Creators: Karabiber, Fethullah, Vecchio, Pietro, Grassi, Giuseppe

File Type: pdf | Filesize: 768.3 KB | Date Added: 2012-08-23 | Date Created: 2011-09-21

Abstract 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.