Method for identifying a person from information contained in a database characterized in that it includes at least the following steps: - generating or using a table containing summary indexes corresponding to a set of intervals around a class midpoint,, - enrolling several biometric data items by carrying out the following steps: - for each biometric data item, calculating a binary template linked to each characteristic parameter of a biometric data item,, - using a hashing method in order to obtain several indexes for each binary template,, - for each index obtained for a biometric data item, inserting an identifier corresponding to the biometric data item minimizing the Hamming distance between the index in question and the summary indexes bounding a bin, in order to obtain a table containing pairs {biometric data item identifier, person identifier},, - capturing at least one biometric data item specific to the person by means of an appropriate sensor and calculating a binary template, (402, 405), - searching in the table for the closest biometric data item or items, comparing the captured biometric data item with the biometric data items of the database, generating an identification result in the case of correspondence between said compared data items or of non-identification of the person, (404, 406), and processing the result obtained. - generating or using a table containing summary indexes corresponding to a set of intervals around a class midpoint,, - enrolling several biometric data items by carrying out the following steps: - for each biometric data item, calculating a binary template linked to each characteristic parameter of a biometric data item,, - using a hashing method in order to obtain several indexes for each binary template,, - for each index obtained for a biometric data item, inserting an identifier corresponding to the biometric data item minimizing the Hamming distance between the index in question and the summary indexes bounding a bin, in order to obtain a table containing pairs {biometric data item identifier, person identifier},, - capturing at least one biometric data item specific to the person by means of an appropriate sensor and calculating a binary template, (402, 405), - searching in the table for the closest biometric data item or items, comparing the captured biometric data item with the biometric data items of the database, generating an identification result in the case of correspondence between said compared data items or of non-identification of the person, (404, 406), and processing the result obtained. - for each biometric data item, calculating a binary template linked to each characteristic parameter of a biometric data item,, - using a hashing method in order to obtain several indexes for each binary template,, - for each index obtained for a biometric data item, inserting an identifier corresponding to the biometric data item minimizing the Hamming distance between the index in question and the summary indexes bounding a bin, in order to obtain a table containing pairs {biometric data item identifier, person identifier},, - capturing at least one biometric data item specific to the person by means of an appropriate sensor and calculating a binary template, (402, 405), - searching in the table for the closest biometric data item or items, comparing the captured biometric data item with the biometric data items of the database, generating an identification result in the case of correspondence between said compared data items or of non-identification of the person, (404, 406), and processing the result obtained.