3/25/2023 0 Comments Gamma color machine visionSuch process was successfully tested on the 3D digitization of 10 km of historical porticoes, but its applicability demonstrated some bottlenecks mainly due to the lack of automation in many steps. The methodology improves what presented in where a process for the color acquisition and management during the generation of 3D AH models was proposed. This includes a radiometric improvement of the image quality and, at the same time, an increase in processing performances for the two central steps of the photogrammetric pipeline (i.e., image orientation and dense image matching). Results of the presented image-based 3D reconstruction of complex architectures (historical buildings with porticoes in Bologna) achieved with the presented methodology: ( a) Palazzina in S.Tecla ( b) Palazzo dell’Archiginnasio ( c) Palazzo Assicurazioni Generali. Furthermore, as automation in image processing increases continuously, high-quality image radiometry is becoming fundamental to allow automated tasks to perform correctly and to have successful and high-quality 3D photogrammetric reconstructions. These difficulties increase when the problem of chromatic and tonal reproduction is addressed to the context of reality-based 3D modeling and visualization. Therefore, designing a basis set of lighting conditions it’s impractical. Moreover, the wide range of materials in historical buildings and monuments façades leads to different values of light reflection, porosity, etc., notwithstanding the fact that the same material reacts to light in different ways, at different time and place. AH, however, implies outdoor environments, where natural light features are complex and mutable. The best results are achieved with controlled light sources (i.e., artificial) in indoor environments, where the knowledge of the illumination allows to estimate surface reflectance parameters using image values. The accuracy of the results of chromatic and tonal properties determination depends on several variables (i.e., illumination during the acquisition step, technical features of the imaging system, mathematical representation of color information throughout the acquisition and reproduction workflow, etc.). These can be determined taking into account that the values of a color in an image are the result of the interaction of incident illumination, object geometry, object reflectance, lens and camera transfer function. Nowadays, the problem of an accurate color description and reproduction using images could be depicted as the faithful determination of chromatic and tonal properties of the color. These achievements improve and speed-up the image-based 3D reconstruction pipeline, particularly in the Architectural Heritage (AH) field, but none of them provides the solution to the problem of accurate color reproduction using automated processes. These progresses allow today to reconstruct large scenes from image sequences readily and at low cost. In the last years major progress has been achieved in the main areas of the automatic photogrammetric pipeline, i.e., scalable tie point extraction, large-scale bundle adjustment and dense point clouds generation, i.e., the core components of the photogrammetric pipeline. A series of tests are presented to demonstrate the efficiency of the developed methodology and to evaluate color accuracy (‘color characterization’). The innovative aspects of the article are: complete automation, better color target detection, a MATLAB implementation of the ACR scripts created by Fraser and the use of a specific weighted polynomial regression. The suggested solution aims to achieve a robust automatic color balance and exposure equalization, stability of the RGB-to-gray image conversion and faithful color appearance of a digitized artifact. In this contribution, we present an automated solution developed to improve the radiometric quality of an image datasets and the performances of two main steps of the photogrammetric pipeline (camera orientation and dense image matching). Image colors are important during the data processing as they affect algorithm outcomes, therefore their correct treatment, reduction and enhancement is fundamental. Ensuring color fidelity in image-based 3D modeling of heritage scenarios is nowadays still an open research matter.
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