Title :
Shadow Removal for Background Subtraction Using Illumination Invariant Measures
Author :
Chulhee Lee ; Sangwook Lee ; Jiheon Ok ; Jaeho Lee
Author_Institution :
Dept. of Electr. & Electron. Eng., Yonsei Univ., Seoul, South Korea
Abstract :
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.
Keywords :
image colour analysis; lighting; object detection; object tracking; background subtraction method; illumination invariant measures; object detection; object tracking; reference background image; shadow removal method; static background environment; Correlation; Gaussian mixture model; Image color analysis; Image quality; Lighting; Neural networks; background subtraction; shadow removal;
Conference_Titel :
Intelligent Systems Modelling & Simulation (ISMS), 2013 4th International Conference on
Conference_Location :
Bangkok
Print_ISBN :
978-1-4673-5653-4
DOI :
10.1109/ISMS.2013.33