Shadows attenuation for robust object recognition

Abstract

Shadows are useful for synthetic images in order to increase extrinsically reality in image generation. However, in natural images, object recognition and segmentation are often negatively affected by cast shadows. Since shadows are a physical phenomena observed in most natural scenes, we propose a fast and reliable procedure to detect and attenuate shadows effects based on color/brightness density. Detected shadows are attenuated by modifying locally brightness and color that have the same color/brightness density. Some color artifacts (false colors on shadows) produced by the acquisition devices have been detected and discussed, and it has been noticed that they may affect some of the classical shadow removal methods. Finally, some experimental results of the proposed shadow attenuation method in real images are presented and evaluated. © Springer-Verlag Berlin Heidelberg 2007.