arXiv Analytics

Sign in

arXiv:1807.04352 [cs.CV]AbstractReferencesReviewsResources

A Reflectance Based Method For Shadow Detection and Removal

Sri Kalyan Yarlagadda, Fengqing Zhu

Published 2018-07-11Version 1

Shadows are common aspect of images and when left undetected can hinder scene understanding and visual processing. We propose a simple yet effective approach based on reflectance to detect shadows from single image. An image is first segmented and based on the reflectance, illumination and texture characteristics, segments pairs are identified as shadow and non-shadow pairs. The proposed method is tested on two publicly available and widely used datasets. Our method achieves higher accuracy in detecting shadows compared to previous reported methods despite requiring fewer parameters. We also show results of shadow-free images by relighting the pixels in the detected shadow regions.

Comments: Presented at the 2018 IEEE Southwest Symposium on Image Analysis and Interpretation
Categories: cs.CV
Related articles: Most relevant | Search more
arXiv:2311.08891 [cs.CV] (Published 2023-11-15)
AdapterShadow: Adapting Segment Anything Model for Shadow Detection
arXiv:2101.01713 [cs.CV] (Published 2021-01-05)
Learning from Synthetic Shadows for Shadow Detection and Removal
arXiv:1805.04635 [cs.CV] (Published 2018-05-12)
Direction-aware Spatial Context Features for Shadow Detection and Removal