Illumination and Reflectance Estimation with its Application in Foreground Detection.
In this paper, we introduce a novel approach to estimate the illumination and reflectance of an image. The approach is based on illumination-reflectance model and wavelet theory. We use a homomorphic wavelet filter (HWF) and define a wavelet quotient image (WQI) model based on dyadic wavelet transform. The illumination and reflectance components are estimated by using HWF and WQI, respectively. Based on the illumination and reflectance estimation we develop an algorithm to segment sows in grayscale video recordings which are captured in complex farrowing pens. Experimental results demonstrate that the algorithm can be applied to detect the domestic animals in complex environments such as light changes, motionless foreground objects and dynamic background.
Department of Animal Science, Aarhus University, 8830 Tjele, Denmark. gangjun.tu@agrsci.dk.
Gang Jun
GJ
Tu
Department of Engineering, Aarhus University, 8000 Aarhus C, Denmark. hka@eng.au.dk.
Henrik
H
Karstoft
Department of Animal Science, Aarhus University, 8830 Tjele, Denmark. lene.juulpedersen@anis.au.dk.
Lene Juul
LJ
Pedersen
Department of Animal Science, Aarhus University, 8830 Tjele, Denmark. erik.jorgensen@anis.au.dk.
Erik
E
Jørgensen
D000465:Algorithms; D000818:Animals; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008029:Lighting / Q000145:classification*; D013552:Swine; D014741:Video Recording / Q000379:methods*
foreground detection; grayscale video recordings; homomorphic wavelet filter; illumination and reflectance estimation; wavelet quotient image model