Tuyển tập các báo cáo nghiên cứu về hóa học được đăng trên tạp chí hóa hoc quốc tế đề tài : Segmentation algorithm via Cellular Neural/ Nonlinear Network: implementation on Bioinspired hardware platform | Karabiber et al. EURASIP Journal on Advances in Signal Processing 2011 2011 69 http content 2011 1 69 o EURASIP Journal on Advances in Signal Processing a SpringerOpen Journal RESEARCH Open Access Segmentation algorithm via Cellular Neural Nonlinear Network implementation on Bioinspired hardware platform Fethullah Karabiber1 Pietro Vecchio2 and Giuseppe Grassi2 Abstract The Bio-inspired Bi-i Cellular Vision System is a computing platform consisting of sensing array sensingprocessing 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. Keywords Cellular Neural Nonlinear Networks image segmentation Bio-inspired hardware platform 1. Introduction Due to the recent advances in communication technologies the interest in video contents has increased significantly and it has become more and more important to automatically analyze and understand video contents using computer vision techniques. In this regard segmentation is essentially the first step toward many image analysis and computer vision problems 1-15 . With the recent advances in several new multimedia applications there is the need to develop segmentation algorithms running on efficient hardware platforms 16-18 . To this purpose in 16 an algorithm for the real-time segmentation of endoscopic images running on a special-purpose hardware architecture is .
