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A fingerprint is the feature pattern of one finger. It is believed with strong evidence that each fingerprint is unique. Each person has his own fingerprints with the permanent uniqueness. So fingerprints have being used for identification and forensic investigation for a long time. This book explores new approaches for designing the various stages of fingerprint classification and identification system. Readers will see how to use models for: - Fingerprint ridges restoration. - Extraction of structural and statistical features of a fingerprint. - Supervised fingerprints classification based on an artificial neural network (ANN)that combines the structural and statistical features of a fingerprint. - Detection of the core point of a fingerprint using an ANN model. - Fingerprints score matching based on the comparison of the relational curves which join the detected minutiae of each fingerprint. Curve matching uses string matching and T-test to generate a list of fingerprint candidates. All topics in this book are organized to be easy to understand. The practical emphasis is reinforced with many illustrative examples for each stage of the fingerprint identification system.