Analysis of Histogram Asymmetry for Waste Recognition

Janusz Bobulski; Kamila Pasternak

doi:10.14313/jamris-2026-007

Abstract

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

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Analysis of Histogram Asymmetry for Waste Recognition

Abstract

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