Shadow Extraction Method Based on Multi-Information Fusion and Discrete Wavelet Transform

Abstract

Shadow occlusion problem has been a hot research topic in fringe projection profilometry (FPP). Since the shadow area cannot be covered by fringe patterns and is easy to induce error, it should be identified and removed. The key to shadow extraction is to determine an accurate shadow threshold. Additionally, the threshold is expected to be automatically adjusted as the brightness changes. In this paper, we put forward a novel shadow extraction method based on 2D discrete wavelet transform (SE-DWT) to suppress outlier points caused by the shadow area. Meanwhile, the multi-information fusion strategy is presented to improve the anti-interference performance and the accuracy of shadow segmentation. More importantly, unlike the conventional methods that determine the shadow threshold based on the light intensity, we make full of the high frequency property of shadow on the phase map, and convert the problem of shadow segmentation into the problem of frequency analysis. Furthermore, the shadow threshold can be determined by analyzing the discrete shadow area. Finally, we can utilize the shadow threshold to binarize the background image, and obtain a continuous shadow mask. The experimental results demonstrate that the proposed method can dynamically adjust the shadow threshold under different brightness, contrast and positions, and can obtain an accurate shadow mask.