Implementation of a cellular neural network-based segmentation algorithm on the bio-inspired vision system

Karabiber F., GRASSI G., VECCHIO P., Arik S., Yalçın M. E.

JOURNAL OF ELECTRONIC IMAGING, vol.20, no.1, 2011 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 20 Issue: 1
  • Publication Date: 2011
  • Doi Number: 10.1117/1.3533327
  • Journal Name: JOURNAL OF ELECTRONIC IMAGING
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Istanbul University Affiliated: Yes

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 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]