Recent years, there has been an increase in the number of high-rise buildings, and subsequently, the interest in external wall cleaning methods has similarly increased. While a number of exterior wall cleaning robots are being developed, a method to detect contaminants on the exterior walls is still required. The exteriors of most high-rise buildings today take the form of a window curtain-wall made of translucent glass. Detecting dust on translucent glass is a significant challenge. Here, we have attempted to overcome this challenge using image processing, inspired by the fact that people typically use just the 'naked eye' to recognize dust on windows. In this paper, we propose a method that detects dust through simple image processing techniques and estimates its density. This method only uses processing techniques that are not significantly restricted by global brightness and background, making it easily applicable in outdoor conditions. Dust separation was performed using a median filter, and dust density was estimated through a mean shift analysis technique. This dust detection method can perform dust separation and density estimation using only an image of the dust on a translucent window with blurry background.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8881614PMC
http://dx.doi.org/10.1038/s41598-022-07235-yDOI Listing

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