Shadow Removal for Background Subtraction Using Illumination Invariant Measures
Chulhee Lee, Sangwook Lee, Jiheon Ok, Jaeho Lee · 2013
In this paper, we propose methods for shadow removal in static background environment. Accurate background subtraction is essential to detect and track various objects. Shadow and objects similar in color are major problems in background subtraction and tracking. In order to address these problems, we propose shadow removal method for background subtraction using illumination invariant measures. First, we computed a reference background image and the illumination invariant measures were applied to the reference background image and an input image. We compared the proposed method with some existing background subtraction methods. The experimental results showed that the proposed method produced more accurate results.