Machine vision for automated optical recognition and classification of pollen grains or other singulated microscopic objects

Abstract

The location and identification of singulated objects on microscope slides is a problem that is common to many applications, including recognition of pollen. In this paper, we describe a working system to solve this problem and demonstrate that it can be used to effectively locate pollen grains on slides, focus on them, photograph them, and then identify them based on a trained neural network. Our system aims to remove the need for laborious, time-consuming, and inaccurate counting of pollen grains by humans with a low-cost machine solution. It can deal with slides obtained using different preparation techniques and media. As well as describing the system, we present positive test results, including a comparision with human experts on the classification and counting of pollen on slides.