Graduation Semester and Year




Document Type


Degree Name

Master of Science in Electrical Engineering


Electrical Engineering

First Advisor

Kamisetty R Rao


Although inkless methods for taking fingerprint impressions are now available, these methods still suffer from the positional shifting caused by the skin elasticity. The non cooperative attitude of suspects or criminals also leads to smearing in parts of the fingerprint impressions. Thus a substantial amount of research reported in the literature on fingerprint identification is devoted to image enhancement techniques.The important step in fingerprint matching is the reliable fingerprint recognition. Automatic Fingerprint Recognition System relies on the input fingerprint for feature extraction. Hence, the effectiveness of feature extraction relies heavily on the quality of input fingerprint images. In this thesis adaptive filtering in frequency domain in order to enhance fingerprint image is proposed.Several stages of processing take place when an Automated Fingerprint Identification System (AFIS) is used to match an unknown fingerprint.1) The fingerprint is first enhanced to remove noisy and any irrelevant information.2) The enhanced image is then encoded into a form suitable for comparison with the records held in the database. The encoded data consists of various key information of the fingerprint image like its minutiae.3) Matching is then performed by comparing the encoded record against those held in the database.4) Verification stage is performed wherein a fingerprint expert visually compares the unknown print with the candidates' fingerprints.In this thesis Gabor filter is used for fingerprint enhancement technique. Because of its frequency selective and orientation selective properties it proves to be useful for fingerprint enhancement. The primary advantage of the approach is improved translation and rotation invariance.


Electrical and Computer Engineering | Engineering


Degree granted by The University of Texas at Arlington