Analysis of Histogram Asymmetry for Waste Recognition

Abstract

Despite many years of effort and research, the problem of waste management remains. So far, no fully effective waste management system has been developed. Many programs and projects improve statistics on the percentage of waste recycled each year. In these efforts, it is worth using modern computer vision techniques supported by artificial intelligence. In the article, we present a method of identifying plastic waste based on the asymmetry analysis of the histogram of images containing the waste. The method is simple but effective (94%), which allows it to be implemented on devices with low computing power, in particular on microcomputers. Such a device will be used at home and in waste sorting plants.