<p>Digital fringe projection (DFP) methods are commonly used to obtain high-accuracy shape measurements of opaque, diffusely-reflective objects. While some objects may have constant texture across its surface, this is not true for all; many measured objects may have high-contrast texture caused by edges of dark- and light-colored sections of the object. In these high-contrast areas, a phase artifact has been consistently observed, which in turn creates a specific measurement error that is sometimes referred to as ``discontinuity-induced measurement artifacts" (DMA). Our study indicated that this error is most likely caused by camera defocusing, which produces a Gaussian point spread function (PSF) that is convoluted across every captured image, thus creating an phase artifact shaped like a Gaussian function. Based on this finding, this thesis outlines a method for removing this error via Gaussian curve fitting on the affected regions. These regions can be found by locating large spikes in the image intensity gradient, which directly correspond to the edge of the phase artifact, and then using a weighted least squared method to fit a Gaussian function to the affected area. We propose to use this error removal method in two ways: first, to remove errors on a checkerboard calibration target in order to increase calibration accuracy; and second, to directly remove errors in high-contrast areas in order to decrease shape measurement error. Experimental results demonstrate that the proposed method succeeds in decreasing calibration error for a checkerboard calibration target by as much as 12\%. Shape measurement experiments were not only conducted across simple, flat boards, but also more complex surfaces, such as that of a coffee mug. This thesis will show that this measurement error can be significantly decreased for both simple and complex surfaces.</p>