An Efficient and Robust Moving Shadow Removal Algorithm and Its Applications in ITS. (8th June 2010)

• Record Type: Journal Article
• Authors: Lin Lin, Chin-Teng Chin-Teng; Yang Yang, Chien-Ting Chien-Ting; Shou Shou, Yu-Wen Yu-Wen; Shen Shen, Tzu-Kuei Tzu-Kuei
• Other Names: van Nevel van Nevel Alan Alan Academic Editor.
• Is Part Of: EURASIP journal on advances in signal processing. Volume 2010(2010)
• Publication Date: 2010-06-08
• Subjects: Signal processing -- Periodicals; Traitement du signal; Signal processing; Periodicals; 621.3822
• DOI: 10.1155/2010/945130
• Languages: English
• ISSNs: 1687-6172

Abstract

Abstract : We propose an efficient algorithm for removing shadows of moving vehicles caused by non-uniform distributions of light reflections in the daytime. This paper presents a brand-new and complete structure in feature combination as well as analysis for orientating and labeling moving shadows so as to extract the defined objects in foregrounds more easily in each snapshot of the original files of videos which are acquired in the real traffic situations. Moreover, we make use of Gaussian Mixture Model (GMM) for background removal and detection of moving shadows in our tested images, and define two indices for characterizing non-shadowed regions where one indicates the characteristics of lines and the other index can be characterized by the information in gray scales of images which helps us to build a newly defined set of darkening ratios (modified darkening factors) based on Gaussian models. To prove the effectiveness of our moving shadow algorithm, we carry it out with a practical application of traffic flow detection in ITS (Intelligent Transportation System)—vehicle counting. Our algorithm shows the faster processing speed, 13.84 ms/frame, and can improve the accuracy rate in 4% ~ 10% for our three tested videos in the experimental results of vehicle counting.