A motion constraint equation under space-varying or time-varying illumination
Pattern Recognition Letters
A neural-vision based approach to measure traffic queue parameters in real-time
Pattern Recognition Letters
Robot Vision
Digital Image Processing
Radiometric CCD camera calibration and noise estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
The study of logarithmic image processing model and its application to image enhancement
IEEE Transactions on Image Processing
An improved vehicle classification method based on Gabor features
Intelligent information processing II
EURASIP Journal on Applied Signal Processing
Moving object segmentation by background subtraction and temporal analysis
Image and Vision Computing
Implementation of digital electronic arithmetic and its application
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Motion detection via change-point detection for cumulative histograms of ratio images
Pattern Recognition Letters
Implementation of Digital Electronic Arithmetics and its application in image processing
Computers and Electrical Engineering
Shedding light on shadow: real-time interactive artworks based on cast shadows or silhouettes
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Communication supporting system in a classroom environment for the hearing impaired
ICCHP'06 Proceedings of the 10th international conference on Computers Helping People with Special Needs
ETHOWATCHER: validation of a tool for behavioral and video-tracking analysis in laboratory animals
Computers in Biology and Medicine
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Background subtraction is widely used as the basis for moving object extraction from image sequences. For traditional background subtraction, the standard intensities in interested images are compared to those in the reference image. As standard intensity can be expressed as the multiplication of illumination and reflectance, the logarithmic intensity is therefore the addition of logarithmic illumination and logarithmic reflectance, which are easier to be separated and analyzed than the multiplication of illumination and reflectance. In this paper, background subtraction based on logarithmic intensities is proposed. Experimental results show that background subtraction based on logarithmic intensities is superior to traditional background subtraction in producing difference images with better quality. In addition, the threshold selection is less critical with the proposed background subtraction scheme.