The study of the different engineering materials according to their mechanical and dynamic characteristics has become an area of research interest in recent years. Several studies have verified that the mechanical properties of the material are directly affected by the distribution and size of the particles that compose it. Such is the case of asphalt mixtures. For this reason, different digital tools have been developed in order to be able to detect the structural components of the elements in a precise, clear and efficient manner. In this work, a segmentation model is developed for different types of dense-graded asphalt mixtures with grain sizes from 9.5 mm to 0.0075 mm, using sieve size reconstruction of the laboratory production curve. The laboratory curve is used to validate the particles detection model that uses morphological operations for elements separation. All this with the objective of developing a versatile tool for the analysis and study of pavement structures in a non-destructive test. The results show that the model presented in this work is able to segment elements with an area greater than 0.0324 mm2 and reproduce the sieve size curves of the mixtures with a high percentage of precision.
Present paper is a continuation of works on evaluation of red, green, blue (RGB) to hue, saturation, intensity (HSI) colour space transformation in regard to digital image processing application in optical measurements methods. HSI colour space seems to be the most suitable domain for engineering applications due to its immunity to non-uniform lightning. Previous stages referred to the analysis of various RGB to HSI colour space transformations equivalence and programming platform configuration influence on the algorithms execution. The main purpose of this step is to understand the influence of computer processor architecture on the computing time, since analysis of images requires considerable computer resources. The technical development of computer components is very fast and selection of particular processor architecture can be an advantage for fastening the image analysis and then the measurements results. In this paper the colour space transformation algorithms, their complexity and execution time are discussed. The most common algorithms were compared with the authors own one. Computing time was considered as the main criterion taking into account a technical advancement of two computer processor architectures. It was shown that proposed algorithm was characterized by shorter execution time than in reported previously results.