Table 3.

A "one user" procedure of metric identification

	Images (provided by multiple users)
Step 1	Obtaining reference images from a web data base
Step 2	Obtaining images of unknown specimens
	Digitization (performed by a single user)
Step 3	Digitizing the images of reference (reference coordinates)
Step 4	Digitizing the images of the unknown specimens (unknown coordinates)
	Classification
Procrustes
Step 5	Pairwise Procrustes distances between each unknown and each reference image
Mahalanobis
Step 6*	Computing shape variables on the combined sets of coordinates obtained from step 3 and one unknown specimen obtained from step 4
Step 7	Computing a discriminant model using the reference shape variables, exclusively (a partition of data from step 6)
Step 8	Entering to the discriminant model the shape variables of the unknown specimen (a partition of data from step 6)
Go to Step 6 for the next unknown specimen.

General steps implemented in the CLIC package, relevant to the geometric approach: digitization (Steps 3 and 4, module COO of the CLIC package), the Procrustes classification (Step 5, module MOG of CLIC) and the discriminant analysis (Steps 6 and 7, module MOG) to identify organisms using mean reference pictures (Step 1) and own pictures (Step 2). The step 2 refers to the field and/or laboratory activities of the biologist: for entomologists, it generally requires the traditional tasks of collecting, dissecting and mounting insects. (*) To reduce multidimensionality, the number of shape variables (Step 6) can be reduced by selecting a set of few first relative warps (RW, i.e. principal components of partial warps). The MOG module automatically selects a number of RW lower than the smallest sample group.