Automated three-dimensional detection and classification of living organisms using digital holographic microscopy with partial spatial coherent source: application to the monitoring of drinking water resources.

In this paper, we investigate the use of a digital holographic microscope working with partially coherent spatial illumination for an automated detection and classification of living organisms. A robust automatic method based on the computation of propagating matrices is proposed to detect the 3D position of organisms. We apply this procedure to the evaluation of drinking water resources by developing a classification process to identify parasitic protozoan Giardia lamblia cysts among two other similar organisms. By selecting textural features from the quantitative optical phase instead of morphological ones, a robust classifier is built to propose a new method for the unambiguous detection of Giardia lamblia cyst that present a critical contamination risk.