Desarrollo de una aplicación basada en visión 3D para determinar la curva de colapso y la distribución del tamaño de burbujas en espumas asfálticas (2020)
The proper foamed asphalts characterization is a key element that allows understanding properties and characteristics that can affect the performance of the mixtures in their diferent applications. The application fi elds of image processing and computer vision are increasing, due to the versatility of the techniques used, since they make the processes more accurate and reliable, minimizing human intervention. This work presents a tool that implements several methods to determine conventional and unconventional parameters that allow the characterization of foamed asphalts. A semi-automatic method based on scene geometry is implemented to determine the parameters of the collapse curve, expansion ratio and half-life. Techniques based on image processing and Machine Learning are implemented to estimate the bubble size distribution in foamed asphalts.