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Volume 13 / Issue 3

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DOI:   10.3217/jucs-013-03-0363


Real-time Architecture for Robust Motion Estimation under Varying Illumination Conditions

Javier Díaz (University of Granada, Spain)

Eduardo Ros (University of Granada, Spain)

Rafael Rodriguez-Gomez (University of Granada, Spain)

Begoña del Pino (University of Granada, Spain)

Abstract: 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.

Keywords: optical flow, real-time image processing, reconfigurable devices (FPGAs), robust illumination systems

Categories: C.1.3, C.3, I.4.8, I.5.4