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This paper describes a biometric personal authentication method, using a pair of right and left sole pressure distribution changes, while walking. This system acquires sole pressure distribution changes via a mat type load distribution sensor, and does personal authentication. We employ twelve features based on the shape of a footprint, and twenty seven features based on weight movement for sole pressure data. Fuzzy if-then rules for each registered person are introduced, within which, their parameters are statistically determined in the learning process. We calculate the fuzzy degree of a pair of right and left sole pressure data for any registered person, and identify the walking person as the person with the highest fuzzy degree; the fuzzy degree being higher than a threshold. We employed 90 volunteers and authenticated them. We evaluate the proposed fuzzy method by five hold cross validation on which low false rejection and false acceptance rates are achieved. Thus, this fuzzy logic approach is precise for this biometric system

Fuzzy-logic is precise—Its application to biometric system