Method to identify objects by uniquely using an optical image of the microstructure of their surface 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 area of interest, having a random identifying microstructure, which considered structure size being below 1mm. the acquisition phase comprising the steps of, for each object to be later identified: - digitally acquiring a two-dimensional template image of the object containing an identifying microstructure, said acquisition being based on the parameter settings and using sampling on a uniformly spaced orthogonal grid of at least one color component, - preprocessing the image in order to remove macroscopic color variations by applying a flattening function on said template, - storing in a reference database the preprocessed template image along with at least one downsampled template versions, the identification phase comprising the steps of, for an object to be identified: - digitally acquiring a two-dimensional snapshot image of the object to be identified and according to the parameters as the template image, - preprocessing the said snapshot image by applying a flattening function in order to remove macroscopic color variations, - generating at least one downsampled versions of the flattened snapshot image with resolutions according to the resolutions during the acquisitions phase, - cross-correlating the 2D most downsampled version of the flattened snapshot image with the corresponding downsampled templates version stored in the reference database regardless of the relative position in translation, and selecting a set of templates according to the value of the signal to noise ratio of the cross-correlation image, - for the selected templates, cross-correlating the 2D downsampled version of next resolution level of the flattened snapshot image with the downsampled versions of same resolution level of flattened template stored in the reference database which have been chosen in previous stage regardless of the relative position in translation, and selecting a set of templates according to the value of the signal to noise ratio of the cross-correlation image, - repeating previous stage for all available downsampled resolutions - for the selected templates, cross-correlating the 2D flattened snapshot image with the flattened template stored in the reference database regardless of the relative position in translation, and thus identifying the object by finding the best corresponding template which signal to noise ratio value of the cross-corrleation image is above a predefined threshold. - defining for a given set of objects, a resolution, a type of non-coherent light illumination and a location, called area of interest, having a random identifying microstructure, which considered structure size being below 1mm. - digitally acquiring a two-dimensional template image of the object containing an identifying microstructure, said acquisition being based on the parameter settings and using sampling on a uniformly spaced orthogonal grid of at least one color component, - preprocessing the image in order to remove macroscopic color variations by applying a flattening function on said template, - storing in a reference database the preprocessed template image along with at least one downsampled template versions, - digitally acquiring a two-dimensional snapshot image of the object to be identified and according to the parameters as the template image, - preprocessing the said snapshot image by applying a flattening function in order to remove macroscopic color variations, - generating at least one downsampled versions of the flattened snapshot image with resolutions according to the resolutions during the acquisitions phase, - cross-correlating the 2D most downsampled version of the flattened snapshot image with the corresponding downsampled templates version stored in the reference database regardless of the relative position in translation, and selecting a set of templates according to the value of the signal to noise ratio of the cross-correlation image, - for the selected templates, cross-correlating the 2D downsampled version of next resolution level of the flattened snapshot image with the downsampled versions of same resolution level of flattened template stored in the reference database which have been chosen in previous stage regardless of the relative position in translation, and selecting a set of templates according to the value of the signal to noise ratio of the cross-correlation image, - repeating previous stage for all available downsampled resolutions - for the selected templates, cross-correlating the 2D flattened snapshot image with the flattened template stored in the reference database regardless of the relative position in translation, and thus identifying the object by finding the best corresponding template which signal to noise ratio value of the cross-corrleation image is above a predefined threshold.