Skip to Main Content
The Cellular Neural/Nonlinear Network (CNN) paradigm has recently led to a Bio-inspired (Bi-i) Cellular Vision system, which represents a computing platform consisting of sensing, array sensing-processing and digital signal processing. This paper illustrates the implementation of a novel CNN-based segmentation algorithm onto the Bi-i system. The experimental results, carried out for a benchmark video sequence, show the feasibility of the approach, which provides a frame rate of about 26 frame/sec. Finally, comparisons with existing CNN-based methods highlight that the proposed implementation represents a good trade-off between real-time requirements and accuracy.