JUCS - Journal of Universal Computer Science 13(3): 363-376, doi: 10.3217/jucs-013-03-0363
Real-time Architecture for Robust Motion Estimation under Varying Illumination Conditions
expand article infoJavier Díaz, Eduardo Ros, Rafael Rodriguez-Gomez, Begoña del Pino
‡ University of Granada, Granada, Spain
Open Access
Motion estimation from image sequences is a complex problem which requires high computing resources and is highly affected by changes in the illumination conditions in most of the existing approaches. In this contribution we present a high performance system that deals with this limitation. Robustness to varying illumination conditions is achieved by a novel technique that combines a gradient-based optical flow method with a non-parametric image transformation based on the Rank transform. The paper describes this method and quantitatively evaluates its robustness to different illumination changing patterns. This technique has been successfully implemented in a real-time system using reconfigurable hardware. Our contribution presents the computing architecture, including the resources consumption and the obtained performance. The final system is a real-time device capable to computing motion sequences in real-time even in conditions with significant illumination changes. The robustness of the proposed system facilitates its use in multiple potential application fields.
reconfigurable devices (FPGAs), optical flow, real-time image processing, robust illumination systems