An accurate automatic personal authentication is becoming more and more important for the
operation of our electronically interconnected information society [1]. Several systems require
authenticating a person’s identity before giving an access to resources. Biometrics has long been
known as a robust approach for person authentication [2]. With new advances in technologies,
biometrics has becoming emerging technology for authentication of individuals. Biometric system
identifies or verifies a person based on his or her physiological characteristics such as fingerprint,
face, palm print, iris etc or behavioral characteristics such as voice, writing style, and gait.
Theoretically, any human physiological or behavioral characteristic can be used to make a personal
identification as long as it satisfies features like universality, uniqueness, permanence and finally
collectability.
Unlike the possession based and knowledge based personal identification schemes, the biometric
identifiers can not be misplaced, forgotten, guessed or easily forged [3], some examples of
biometric system are fingerprint recognition, face recognition, palm print recognition, voice
recognition etc. Traditional personal identification systems are based on “Something that you
have” e.g. Key or “Something that you know” e.g. Personal Identification Number [PIN], but
biometrics relies on “Something that you are”. Biometric systems used in real world applications
are unimodal [4]. These unimodal biometric systems rely on the evidence of a single source of
information for authentication of person. Though these unimodal biometric systems have many
advantages, it has to face with variety problems like: