Automatic Visual Detection of Incorrect Endoscope Adaptions in Chemical Disinfection Devices

This paper presents a complete analyzing system for detecting incorrect endoscope adaptions prior to the use of chemical disinfection devices to guarantee hygienic standards and to save resources. The adaptions are detected visually with the help of an image registration algorithm based on feature detection algorithms. On top of the processing pipeline, we implemented a k-nearest neighbor algorithm to predict the status of the adaption. The proposed approach shows good results in detecting the adaptions correctly.