Increasing the safety in recycling of construction and demolition waste by using supervised machine learning

Abstract

This paper discusses the possibility of the optical identification of recycled aggregates of construction and demolition waste (CDW) using methods of image processing, spectral analysis and machine learning. The classification performances in colour images shown, that we have to use other added spectral information to solve the recognition task in a satisfactory manner. In addition to investigations on a large colour image dataset first investigations in visible (VIS) and infrared (IR) spectrum were done for analysing significant characteristics in spectrum, which are useful for classification the C&D aggregates.