Computer-vision based pharmaceutical pill recognition on mobile phones
Andreas Daniel Hartl · 2022
In this work we present a mobile computer vision system which simplifies the task of identifying pharmaceutical pills. A single input image of pills on a special markerbased target is processed by an efficient method for object segmentation on structured background. Estimators for the object properties size, shape and color deliver parameters that can be used for querying an online database about an unknown pill. A prototype application is constructed using the Studierstube ES framework, which allows to perform pill recognition on off-the-shelf mobile phones. System runtime and retrieval performance with the estimated features is subsequently evaluated on a realistic test set. The retrieval performance on the exemplarily used Identa database confirms that the system can facilitate the task of mobile pill recognition in a realistic scenario.