Automated Surface Cleaning Evaluation Algorithm

To avoid micro-organisms spreading in hospitals, hand hygiene and hospital environment disinfection and cleaning is considered to prevent the infections. Therefore, CDC provides hand hygiene and surface cleaning evaluation methods to ensure that source of micro-organisms is disposed. Basically, the surface cleaning is evaluated by the cleaning evaluator who identifies the unclean area through the brightness area of fluorescent marker shined by blacklight under a dark room. However, the evaluation errors may occur if the determine surface is barely clean where the fluorescent marker is not completely removed. Moreover, it is very difficult to meet the same evaluation standard if the evaluation is done by human estimation. In addition, it takes long evaluation time via visual evaluation. In this paper, we propose an automated surface cleaning evaluation algorithm that evaluates the surface cleaning automatically by extracting the color image component, blue, which is noticeably bright under the blacklight characteristic. In the experiment, we compare the performance of the proposed algorithm using blue component to other image components. As a result, the proposed algorithm shows the highest accuracy determined by the experienced cleaning evaluator. Moreover, the proposed algorithm shows 4.384 times faster of surface cleaning detection than cleaning evaluator.