18-12-2012, 12:41 PM
SHADOW DETECTION AND REMOVAL
SHADOW DETECTION.ppt (Size: 58.5 KB / Downloads: 41)
INTRODUCTION
The RGB colour model is used in which red, green and
blue light are added together in various ways to reproduce a
broad array of colors. The average colour values of red, green¸
and blue (primary) components in image are obtained. After
this, shadows are identified by comparing average R, G, and
B values with original R, G, and B values of image. The effect
of the presence of a shadow on a particular pixel is that the
representative values in the RGB primary colors are lowered.
This is due to the fact that lower relative numbers represent
darker colour. Thus, the darker areas are considered as
shadows
Transform a RGB image f to a gray one F that is not sensitive to shadows so much compared with the original one.
Separate R, G, B components in the image
Calculate the mean value of the R, G, and B in each region
Find the shadow and non shadow region based on the mean value. Take pixels whose values are larger than the mean value of region as the non shadow background. And pixels whose values are lower than the mean value of region as the non shadow background.
To subtract the minimum channel from the maximum channel, the value of ΔR, ΔG, and ΔB is calculated using the formula.
Binarize the image by considering the threshold T based on the observation that shadows are often darker than the mean value of Xi The final result is an extracted shadow.