Recent advances in information technologies and the increasing proposed security requirements have led to a rapid development of automatic personal identification systems based on biometrics. Biometrics refers to the accurate identification of an individual based on their distinctive physiological (e.g., fingerprint, face, retina, iris) or behavioral (e.g., gait, signature) characteristics [1]. It is inherently more reliable and more capable than traditional token- or knowledge-based methods in distinguishing between an authorized person and a fraudulent impostor. Among all biometric systems, fingerprint recognition is one of the most reliable and promising personal identification technologies. Biometric authentication is highly reliable, because human physical characteristics are much more difficult to spoof: security codes, passwords, hardware key sensors, fast processing equipment and significant memory capacity, so the system are expensive. Biometrics-based authentication caters to diverse applications such as workstation and network access, single sign-on, application access, data protection, remote resource access, transaction security, and web security. Furthermore, the promise of e-commerce and e-government can be achieved through the use of strong personal authentication procedures. Banking electronic security, investments and other financial transactions, retail, law enforcement, healthcare and social services are already benefiting from these technologies. Biometric technologies are expected to play a key role in personal authentication for large-scale enterprise network authentication environments, point of sale and application security. Used alone or integrated with...... half of the document ......d recently [4, 5]. Erasable biometrics uses transformed or intentionally distorted biometric data instead of the original biometric data to identify the person. When a set of biometric data is compromised, you can delete it and regenerate a new set of biometric data. Several key aspects that generate erasable biometric data can be defined as modifiability (how dissimilar the transformed data is compared to the original data), non-invertibility (the transformed biometric data should not be easily converted back to the original biometric data even if the transformation method is known and transformed data is data), reproducibility (we should be able to generate many different erasable patterns from the original data), performance degradation (performance when using transformed patterns should not be degraded much).