A Tree System Approach for Fingerprint Pattern Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special memorial issue for Professor King-Sun Fu
Line thinning by line following
Pattern Recognition Letters
An approach to fingerprint filter design
Pattern Recognition
The Design and Use of Steerable Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Steerable-scalable kernels for edge detection and junction analysis
Image and Vision Computing - Special issue: 2nd European Conference on Computer Vision
On-Line Fingerprint Verification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fingerprint Image Enhancement: Algorithm and Performance Evaluation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fingerprint Classification by Directional Image Partitioning
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Image Processing
Direct Gray-Scale Minutiae Detection In Fingerprints
IEEE Transactions on Pattern Analysis and Machine Intelligence
WACV '96 Proceedings of the 3rd IEEE Workshop on Applications of Computer Vision (WACV '96)
Filterbank-based fingerprint matching
IEEE Transactions on Image Processing
| Hi-index | 0.00 |
Extracting minutia and other features from fingerprint images is one of the most important steps in automatic fingerprint identification and classification. This paper proposes a method for the generation of long and secure code that may be used for multi-purpose applications, such as ATM, coded door locks and other security measures. The method consists of two phases; the first phase is carried out using fingerprint image enhancement and thinning. The second phase consists of extracting minutia, ridge ending, bifurcation and all other features in order to produce initial pattern. Finally the multi-purposes secure code is generated by applying the one-way MD5 hash function on that pattern. The achieved results are discussed for security improvement. The proposed technique also shows considerable improvement in the minutia detection process in terms of both efficiency and speed.