Hardware architecture and design methods

This project is devoted to research on methods for design automation and on hardware architecture for machine vision systems. Scientific results on algorithms for machine vision cannot be exploited for high speed applications unless attention is also paid on implementation issues. System performance such as speed, power and latency can be important design metrics for application areas such as robotics, automotive industry or battery powered systems. These important design considerations are complex and cannot just be ignored with a pure research focus on algorithms. Field Programmable Gate Arrays (FPGA) has developed into a heterogeneous computational platform having memory, computational blocks as well as embedded microprocessors. If to make efficient use of these emerging more complex hardware, we need to invest in the development of better methods for design automation. Otherwise the NRE cost will dominate and limit their use.



Senior researchers
Dr. Najeem Lawal
Prof. Mattias O’Nils
Dr. Benny Thörnberg

PhD students
Waheed Malik


Visual Eyes AB
Meeq AB