Biometrics refers to automated recognition of individuals based on their biological and behavioral characteristics. Biometric systems are widely used for security. They are used in forensic and commercial applications. Among all biometric techniques, fingerprint recognition is the most widely used for personal identification systems due to its permanence and uniqueness. But biometric systems are vulnerable to certain type of attacks. Spoofing refers to the fraudulent action by an unauthorized person into biometric systems using fake input that reproduces one of the authorized person's biometric input.Spoof detection provides extra level of authentication to biometrics. It is used to prevent forgeries. The fingerprint spoof detection is performed by measuring the following quality features of fingerprint. They are Spatial Coherence, Clustering Factor, Gabor Features, Uniformity of Frequency field, Ridge frequency, Direction map and Contrast map. This approach is based on fingerprint image quality. This technique is software based as it requires no external hardware. This approach is inexpensive.

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Biometrics is used for authentication purpose. Among the various types of biometrics, fingerprint is the most widely accepted biometrics. Biometric systems have several advantages when compared to classical methods such as passwords. Biometric system is vulnerable to various types of attacks. This paper proposes a method to avoid the sensor level attack. This method uses limited ring wedge spectral energy, Inhomogenity and Directional Contrast. The limited ring wedge spectral density is the global quality measure. Inhomogenity and Directional Contrast are the local quality measures.