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Fuzzy hamming distance is successfully used in a content-based image retrieval (CBIR) system as a similarity measure. The system performs an m × n partitioning of the compared images and for each partition pairs evaluates FHD. In the last step, the FHD are defuzzified and the results are combined in a final score. In order to take full advantage of the use of fuzzy sets, the current study investigates the possibility of reversing the order of the defuzzification and aggregation steps: aggregate fuzzy set and defuzzify final result for ranking. Several t-norm and associated t-conorm aggregation operators are experimented with. The results are illustrated on retrieval operations from an image database.