Author: Şeref SAĞIROĞLU, Necla ÖZKAYA
Publishing Date: 2005
Volume 20 Issue 3
This work presents an intelligent automatic fingerprint identification and verification system based on Artificial Neural Networks (ANNs). In this work, the design processes of the system have been presented step by step. Fingerprints were first converted into digital images using a specific hardware. They were then processed by a computer. Fingerprint images were divided into grid blocks, and these blocks were classified as image area and background. An effective algorithm was used to detect the fingerprint singularities from gray level fingerprint images. In order to improve the performance of the system, fingerprint image enhancement was performed by using ANN. The adaptive backpropagation with momentum learning algorithm was used to train the ANN models. Binary images were obtained from the enhancement images using a regional binarization algorithm. Binary images were converted to thinned images. Ridge endings and ridge bifurcations of the fingerprints (minutiae) were extracted. A postprocessing algorithm was used to eliminate false minutiae patterns and the fingerprint matching process was finally applied. In order to automatise the system, a software for fingerprint identification and verification was developed in Delphi. The system developed in this work was tested 100 fingerprint images for identification and verification; it achieves the task with high accuracy. It is assumed that the developed system can be used in many security applications.
Key Words: Biometrics; intelligent system; artificial neural networks, fingerprint identification, verification, enhancement, minutiae extracting; singular points; comparison.