Technical Challenges for Biometric Science

The Biometric is the study of physiological or behavioral characteristics used for the identification of a person. These characteristics of a person include the features like fingerprint, face; hand geometry, voice and iris are known as biometrics. Typical physiological features measured include individual’s fingerprints, retina, face, iris and hand. Typical behavioral features that can be measured include voice patterns, handwriting and keystroke dynamics. Basically we can use physiological characteristics than behavioral because behavioral characteristics are changed with age and environment whereas physiological characteristics never changed during whole life. In previous papers the overall matching algorithm were based on the clearly fingerprint images which was not applicable for dusty images, oily images characteristics. When these characteristics are forensics altered dusty images, oily images are challenged. We have all heard about criminals who have altered their fingerprints so as not to be identified by law enforcement because of poor image quality and after long period dust covers the original fingerprint images. This paper focuses on an algorithm for latent fingerprint matching. The aim is to develop an algorithm for latent fingerprint matching using descriptor based Hough transform which is specially for dusty images used in law enforcement lab. Proposed algorithm achieves better accuracy and lower error rate while using the dusty fingerprint image as a biometric data. Keywordsbiometric,fingerprint,physiological,behavioral, hough transform, law enforcement, latent.