Development and improvement of 3D digitizing systems provide for the ability to digitize a growing number of materials and geometrical forms of greater complexity. This paper presents the application of 3D digitizing system using close range photogrammetry on the upper jaw cast in plaster in order to obtain its 3D model. Because of the low visual characteristics of gypsum, such as color and texture, many questions arise about the possibility of applying this particular method to this type of physical models. In order to overcome bad visual properties of gypsum, this paper analyzes the possibility of the photogrammetry method application supported by the projected light texture which is based on patterns in the form of noise-obtained  mathematically modeled functions. In order to determine the selected image for light texture which gives the better results, an experiment was designed and carried out. Only two images were tested. One image is selected based on previous research and the other one was generated by the Matlab function for uniformly distributed random numbers. For validation and a comparative analysis of the results, an object of 3D digitization was generated with and without projected light texture. CAD inspection was applied for the analysis of the obtained 3D digitizing results. 3D model obtained by approved professional optical 3D scanner as a reference was used. The results in this paper confirm better accuracy of 3D models obtained with the use of light textures, but this approach requires additional hardware and setup adjustment for images acquisition.

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Application of 3D CBCT images, computer-aided systems and software in manufacturing custom bone grafts represents the most recent method of guided bone regeneration. This method substantially reduces time of recovery and carries minimum risk of postoperative complications, yet the results fully satisfy the requirements of both the patient and the therapist.

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Small and start-up companies that need product quality control can usually only afford low-cost systems. The main goal of this investigation was to estimate the influence of high dynamic range images as input for the low-cost photogrammetric structure from motion 3D digitization. Various industrial products made of metal or polymer suffer from poor visual texture. To overcome the lack of visual texture and ensure appropriate 3D reconstruction, stochastic image in the form of the light pattern was projected on the product surface. During stochastic pattern projection, a set of low dynamic range and sets of high dynamic range images were captured and processed. In this investigation digital single lens reflex camera that supports five different tonemapping operators to create high dynamic range images were used. Also, high precision measurements on a coordinate measuring machine are performed in order to verify real product geometry. The obtained results showed that reconstructed polygonal 3D models generated from high dynamic range images in this case study don't have a dominant influence on the accuracy when compared to the polygonal 3D model generated from low dynamic range images. In order to estimate 3D models dimensional accuracy, they were compared using computer-aided inspection analysis. The best achieved standard deviation distance was +0.025 mm for 3D model generated based on high dynamic range images compared to the nominal CAD model.