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Wavelet analysis for shadow detection in Fringe Projection Profilometry

机译:边缘投影轮廓测量中的阴影检测小波分析

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Fringe Projection Profilometry (FPP) is the most widely used method for 3D reconstruction. In FPP, the elevation information is deduced from the deformation of the pattern induced by the object. In the shadow areas, no fringe patterns are formed and as a result, the elevation information in these areas cannot be determined resulting in errors in the 3D reconstruction. This paper proposes a new method to detect the occurrences of shadow using the Haar Wavelet for a typical single camera with one projector configuration. The Haar wavelet emphasises the sudden change caused by boundary of the shadow and also shows the non-existence of the pattern in the shadow area. The method detects shadow boundary and differentiates shadow and non-shadow area based on the threshold defined from the statistics of the signal. The method is found more suitable for deformed fringe pattern than Fourier-based shadow detection, as the nature of the signal is non-stationary. The proposed method correctly detects shadow with robustness to the noise power up to 16.9 dB.
机译:条纹投影轮廓测量(FPP)是最广泛使用的3D重建方法。在FPP中,从物体引起的图案的变形推导出升降信息。在阴影区域中,没有形成条纹图案,结果,不能确定这些区域中的高程信息,从而导致3D重建中的错误。本文提出了一种新方法,用于使用一个带有一个投影仪配置的典型单摄像机使用HAAR小波检测阴影发生的新方法。 Haar小波强调阴影边界引起的突然变化,并且还示出了阴影区域中的图案的不存在。该方法检测阴影边界并基于从信号的统计信息定义的阈值来区分阴影和非阴影区域。发现该方法更适合于变形的条纹图案,而不是基于傅里叶的阴影检测,因为信号的性质是非静止的。所提出的方法正确地检测到稳健性的阴影,到噪声功率高达16.9 dB。

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