Abstract: A feature extraction and pattern collation system for statistically analyzing a set of samples of feature vectors to calculate a feature being an index for a pattern identification, which is capable of identifying confusing data with a high robustness. In this system, a storage section stores a feature vector inputted through an input section and a neighborhood vector selection section selects a specific feature vector from the feature vectors existing in the storage section. The specific feature is a neighborhood vector close in distance to the feature vector stored in the storage section. Further, the system is equipped with a feature vector space production section for outputting a partial vector space. The partial vector space is made to maximize the local scattering property of the feature vector when the feature vector is orthogonally projected to that space. The pattern collation system is thus capable of obtaining learning data from a plurlaity of different persons.