2 research outputs found
Adaptive FPGA NoC-based Architecture for Multispectral Image Correlation
An adaptive FPGA architecture based on the NoC (Network-on-Chip) approach is
used for the multispectral image correlation. This architecture must contain
several distance algorithms depending on the characteristics of spectral images
and the precision of the authentication. The analysis of distance algorithms is
required which bases on the algorithmic complexity, result precision, execution
time and the adaptability of the implementation. This paper presents the
comparison of these distance computation algorithms on one spectral database.
The result of a RGB algorithm implementation was discussed
Evaluation and Design Space Exploration of a Time-Division Multiplexed NoC on FPGA for Image Analysis Applications
The aim of this paper is to present an adaptable Fat Tree NoC architecture
for Field Programmable Gate Array (FPGA) designed for image analysis
applications. Traditional NoCs (Network on Chip) are not optimal for dataflow
applications with large amount of data. On the opposite, point to point
communications are designed from the algorithm requirements but they are
expensives in terms of resource and wire. We propose a dedicated communication
architecture for image analysis algorithms. This communication mechanism is a
generic NoC infrastructure dedicated to dataflow image processing applications,
mixing circuit-switching and packet-switching communications. The complete
architecture integrates two dedicated communication architectures and reusable
IP blocks. Communications are based on the NoC concept to support the high
bandwidth required for a large number and type of data