Fingerprint Minutiae Extraction and Compression using LZW Algorithm

For security and surveillance automated personal identification is major issue. We can see a lot varieties of biometric systems like face detection, fingerprint recognition, iris recognition, voice recognition, palm recognition etc. In our project we will only go for fingerprint recognition. Never two peoples have exactly same fingerprints even twins, they are totally unique. The sensors capture the finger prints of humans and convert them into images and a minutiae extraction algorithm extracts the location of minutiae points called termination and bifurcation. A database system stores these patterns and minutiae points of fingerprint. A large storage space required to store bifurcation and termination points for the fingerprint database. LZW compression algorithm has been used to reduce the size of data. With LZW applied on these extracted minutiae points, these minutiae points get encoded which add more security feature.