The purpose of this paper is to demonstrate how a syntactic approach and, in particular, a tree system may be used to represent and classify fingerprint patterns. The fingerprint impressions are subdivided into sampling squares which are preprocessed and postprocessed for feature extraction. A set of regular tree languages is used to describe the fingerprint patterns and a set of tree automata is used to recognize the coded patterns. In order to infer the structural configuration of the encoded fingerprints, a grammatical inference system is developed. This sytem utilizes a simple procedure to infer the numerous substructures and relies on a reachability matrix and a man-machine interactive technique for the inference of complex structures. The 92 fingerprint impressions were used to test the proposed approach. A set of 193 tree grammars was inferred from each sampling square of the 4 × 4 sampling matrix which is capable of generating about 2 × 1034 classes for the fingerprint patterns.

The purpose of this paper is to demonstrate how a syntactic approach and, in particular, a tree system may be used to represent and classify fingerprint patterns. The fingerprint impressions are subdivided into sampling squares which are preprocessed and postprocessed for feature extraction. A set of regular tree languages is used to describe the fingerprint patterns and a set of tree automata is used to recognize the coded patterns. In order to infer the structural configuration of the encoded fingerprints, a grammatical inference system is developed. This system utilizes a simple procedure to infer the numerous substructures and relies on a reachability matrix and a man-machine interactive technique for the inference of complex structures. The 92 fingerprint impressions were used to test the proposed approach. A set of 193 tree grammars was inferred from each sampling square of the 4 × 4 sampling matrix which is capable of generating about 2 × 1034classes for the fingerprint patterns.