Global Illumination Invariant Object Detection With Level Set Based Bimodal Segmentation

In this letter, we propose a new detection method for video surveillance which provides for a robust and real-time working object detection under various global illumination conditions. The proposed scheme needs no manual parameter settings for different illumination conditions, which makes the algorithm applicable to automatic surveillance systems. Two special filters are designed to eliminate the spurious object regions that occur due to the charge coupled device (CCD) noise, making the scheme stable even in very low illumination conditions. We demonstrate the effectiveness of the proposed algorithm experimentally with different illumination conditions, changes in contrast, and noise level.

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