This module is developped at INRIA (Orion).
The goal of this module is to identify the type of the pollen grain from 3D images. The main originality of this approach is the use of 3D images and of palynological knowledge.
The pollen grain recognition is done following two steps:
To accomplish the recognition, it is necessary to work on 3D images and to use deep palynological knowledge. This knowledge describes the pollen types according to their main visible characteristerics and to those which are important for recognition. The strategy used for recognition first detects the pollen grain boundaries in 3D. Then, the main characteristics are searched for according to their location. For example, the top surface is analyzed to understand the ornamentation while the central images help to identify the cytoplasm or the exine thickness. The detection algorithms work on 2D images and validate their result in 3D (i.e. a pore is detected and validated if it appears in several images). Such algorithms use image processing methods like thresholding, gradient analysis, region segmentation, color analysis. Different algorithms are developed to identify a single characteristic with different appearances (a pore is seen differently from the polar view than the equatorial view).