1. Method to identify an object comprising a parameter settings phase, an acquisition phase and an identification phase, the parameter setting phase comprising the steps of: defining for a given set of objects, a resolution, a type of non-coherent light illumination and a location, called region of interest, for the acquired image for which the object's microstructure image contains noise, the acquisition phase comprising the following steps, for each object to be later identified: digitally acquiring a two-dimensional image of the object according to parameter settings through sampling on a uniformly spaced orthogonal grid of at least one color component, applying a flattening function on said template in order to produce a flattened template by removing macroscopic color variations, generating at least one downsampled template version of the flattened template, storing in a reference database the downsampled template version and the flattened template, the identification phase comprising the following steps, for the object to be identified: digitally acquiring a two-dimensional snapshot image according to the same parameters as the template image, applying to the snapshot image the same flattening function as the one applied to the template image in order to produce a flattened snapshot image, generating at least one downsampled version of the flattened snapshot image, cross-correlating the downsampled version of the flattened snapshot image with the corresponding downsampled templates version stored in the reference database, and selecting the templates according to the value of the signal to noise ratio of said cross-correlation, for the selected templates, cross-correlating the flattened snapshot image with the flattened template stored in the reference database, and thus identifying the object by finding the best corresponding template which signal to noise ratio value of said cross-correlation is above a predefined threshold.