Detecting Shadow of Moving Object based on Phong Illumination Model

When detecting moving objects using visible light image sequence, the shadows of moving objects always appear together with moving objects. Shadows usually change with light condition, which brings difficulty for recognizing objects after segmenting image. This text proposes an algorithm to detect shadows in foreground image according to the Phong illumination model. The algorithm combines the brightness information between foreground image and background image to calculate an array of brightness relative variation ratio, detecting shadows using the statistical feature of shadows in the array. The algorithm uses the statistical histogram to describe statistical feature of brightness relative variation ratio, and the Gaussian model to do curve fitting as a description for the shape of statistical histogram. And finally with the property of the fitted function could we find the threshold value of shadows adaptively. Introduction When using popular algorithms to detect moving objects, among those algorithms such as optical flow [1], frame difference [2], background subtraction, usually a frame of image is segmented as foreground image and background image. In foreground image, moving objects and shadows of moving objects always appear together. Among the popular algorithms used for object recognition, shadows are obstacle for achieving accuracy of the feature extracted from objects of the algorithm. How to remove shadows accurately and completely become an important work before further recognition and tracking of moving objects. At present, there are three categories of algorithm to detect shadows, based on color, texture, and statistical information [3]. This text detects shadows based on the illumination features in foreground image according to Phong illumination model. Experiments prove that the algorithm has a good effect and less calculation. Analysis of Shadow Area Illumination Feature According to Phong illumination model [4], brightness reflected from objects mainly comes from ambient light, diffuse reflection light, specular reflection light. Assume I the brightness of object, e I the light intensity of ambient light, s I the light intensity of direct light from light source, a K , b K , c K are the reflection coefficients, θ is the included angle between incident light and the surface normal, α is the included angle between reflected light and gazing direction, s n is the coefficient of specular reflection, so the brightness of object could be defined as Eq. 1. s n a e b s c s I K I K I cos cosθ K I cos α. = + + (1) In real world scenarios, most objects surface are not smooth, hence assume the contribution of specular reflection light for brightness could be ignored, means s n c s K I cos α to be 0. a K and b K could be considered approximately as the same. Assume ( ) F I x, y to be the brightness value of pixel point ( ) x, y in foreground image, ( ) B I x, y to be the brightness value of pixel point ( ) x, y in background image, define the brightness relative variation ratio to be as Eq. 2. International Conference on Information Sciences, Machinery, Materials and Energy (ICISMME 2015) © 2015. The authors Published by Atlantis Press 2019