A novel approach for cast shadow modelling and detection
Nijad A. Al-Najdawi, Helmut Bez, Eran A. Edirisinghe · 2006
Several shadow detection and removal algorithms have been proposed to distinguish between objects and their shadows for computer vision applications, as the design of a fast and efficient algorithm remains a challenge. In this work, based on a physically-derived hypothesis for shadow identification, novel, simple and fast shadow detection algorithms are proposed and implemented in the spatial (pixel) and frequency (Fourier) domains. It is shown that the algorithms effectively remove shadows under various lighting and environmental conditions. The proposed algorithms are able to detect shadows in both umbra and penumbra neighborhoods.