Shadow segmentation and classification in a constrained environment
CVGIP: Image Understanding
Image difference threshold strategies and shadow detection
BMVC '95 Proceedings of the 1995 British conference on Machine vision (Vol. 1)
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Color Recognition in Outdoor Images
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Cast Shadow Removal with GMM for Surface Reflectance Component
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
Shadow removal from a real image based on shadow density
SIGGRAPH '04 ACM SIGGRAPH 2004 Posters
Shadow identification and classification using invariant color models
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03
Detection of moving cast shadows for object segmentation
IEEE Transactions on Multimedia
Image shadow removal using pulse coupled neural network
IEEE Transactions on Neural Networks
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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.