1. A method for identifying characters in a character string image, the method comprising: (i) applying a first Optical Character Recognition engine to provide an identification of characters of at least a first type of characters and zones of at least a second type of characters in the character string image, (ii) applying on the zones of the at least second type of characters a second Optical Character Recognition engine to provide an identification of characters of a second type of characters, and (iii) combining the characters identified by the first Optical Character Recognition engine and by the second Optical Character Recognition engine to obtain the identification of the characters of the character string image, wherein the first Optical Character Recognition engine comprises a segmentation of the character string image into segmentation parts, the segmentation of the character string image into segmentation parts comprising the steps of determining a first starting point coordinate of a pixel contrasting to a background, generating a list of potential character widths dependent on a maximum character width and on characteristics of the portion of the character string image corresponding to the maximum character width, and determining a second portion of the character string image corresponding to the first starting point coordinate and the first width on the list of potential character widths, and wherein the first Optical Character Recognition engine comprises, for each segmentation part, the steps of: (a) applying a first character classification to provide a first plurality of hypotheses on an at least one character represented by the segmentation part and a first plurality of probabilities associated with the first plurality of hypotheses, (b) verifying if the first plurality of hypotheses satisfies at least one condition, (c) if at least one condition is satisfied, applying a second character classification to provide a second plurality of hypotheses on the at least one character represented by the segmentation part and a second plurality of probabilities associated with the second plurality of hypotheses.