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, 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 having statistical property of noise, 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, - masking disturbing elements of the flattened image, - storing in a reference database the preprocessed template image, 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, - retrieving the rotation between the snapshot and the template image using a transform domain, - 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 said cross-correlation 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, - digitally acquiring a two-dimensional template image of the object containing an identifying microstructure having statistical property of noise, 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, - masking disturbing elements of the flattened image, - storing in a reference database the preprocessed template image, - 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, - retrieving the rotation between the snapshot and the template image using a transform domain, - 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 said cross-correlation is above a predefined threshold.