@MASTERSTHESIS\{IMM2016-06925,
    author       = "K. R. Thomsen",
    title        = "Combined {3D,} multispectral, and fluorescence imaging through design of an integrated structural light scanner",
    year         = "2016",
    school       = "Technical University of Denmark, Department of Applied Mathematics and Computer Science",
    address      = "Richard Petersens Plads, Building 324, {DK-}2800 Kgs. Lyngby, Denmark, compute@compute.dtu.dk",
    type         = "",
    note         = "{DTU} supervisors: Jens Michael Carstensen, jmca@dtu.dk ({DTU} Compute) and Anders Bjorholm Dahl, abda@dtu.dk ({DTU} Compute). Industrial cooperator: Videometer A/S",
    url          = "http://www.compute.dtu.dk/English.aspx",
    abstract     = "The goal of the thesis is to design a system for measuring {3D} simultaneously with spectral image recording in the VideometerLab4 instrument, develop analysis algorithms to exploit the combined {3D} and spectral information, and to demonstrate that this can be utilized efficiently in {1-}3 applications. The possible approaches for designing such an integrated {3D} measurement system are discussed and evaluated and an in-depth analysis made of selected types of structured light solutions and time-of-flight technology. A variant of phase shifting profilometry based on Fourier analysis is selected as the most suitable method given the system specifications. The problem of phase unwrapping is also studied and a dual-wavelength solution selected. Algorithms for triangulation of points in {3D} space are discussed and a computationally effective algorithm is derived. The extended acquisition time for additional {3D} measurements are just 0.6 seconds. The accuracy of the systems {3D} reconstructions are analysed and the height error found to be normally distributed around zero with a standard deviation of just 34.7 micrometers. The lateral uncertainty is 25.9 micrometers. An accurate and robust stereo calibration is explained and performed with sub-pixel accuracy for both the camera and the projector. Lastly two specific applications of combined {3D} and spectral data are introduced and evaluated. First a novel algorithm is presented for classification of grains orientation into the categories of either dorsal or ventral and it is shown to be statistically significantly outperforming the {2D} alternative. Segmentation of granular products, such as rice, grains or seeds, are also studied and a modification to the existing {2D} approach presented that are expected to increase the number of correctly segmented grains by 1.5\%."
}