Altuve M.2020-03-262020-03-2620162016 21st Symposium on Signal Processing, Images and Artificial Vision, STSIVA 20169781509037971https://hdl.handle.net/20.500.12585/8976In Fourier Transform Profilometry, a filtering procedure is performed to separate the desired information (first order spectrum) from other unwanted contributions such as the background component (zero-order spectrum). However, if the zero-order spectrum and the high order spectra component interfere the fundamental spectra, the 3D reconstruction precision decreases. In this paper, we test two recently proposed methods for removing the background intensity so as to improve Fourier Transform Profilometry reconstruction precision. The first method is based on the twice piece-wise Hilbert transform. The second is based on Bidimensional Empirical Mode Decomposition, but the decomposition is carried out by morphological operations In this work, we present as a novel contribution, the sequential combination of these two methods for removing the background intensity and other unwanted frequencies close to the first order spectrum, thus obtaining the 3D topography of the object. Encouraging experimental results show the advantage of the proposed method. © 2016 IEEE.Recurso electrónicoapplication/pdfenghttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/conferenceObject10.1109/STSIVA.2016.7743326Contour measurementImage processingInformation filteringMathematical morphologyMathematical transformationsProfilometryVisionBackground componentsBi-dimensional empirical mode decompositionsFiltering proceduresFourier transform profilometryHigh order spectraMorphological operationsSequential combinationThree-dimensional reconstructionSignal processinginfo:eu-repo/semantics/restrictedAccessAtribución-NoComercial 4.0 InternacionalUniversidad Tecnológica de BolívarRepositorio UTB57117284600571922700162432983930036142156300