Banknote validation systems are used to discriminate between genuine and counterfeit banknotes. The paper proposes a one-class classifier for genuine class using a new similarity measure based on the fuzzy Hamming distance. For each banknote several regions are considered (corresponding to security features) and each region is split in m times n partitions, to include position information. The feature space used by the classifier consists of color histograms of each partition. The fuzzy Hamming distance proves to have a good discrimination power being able to completely discriminate between the genuine and counterfeit banknotes