Keywords : Fingerprint

Distinguish of Fingerprint Based on Artificial Neural Networks

Zahraa Maen Al-Qattanz

AL-Rafidain Journal of Computer Sciences and Mathematics, 2014, Volume 11, Issue 1, Pages 143-162
DOI: 10.33899/csmj.2014.163744

In this research use one of artificial intelligence techniques which is artificial neural networks was used to distinguish fingerprint from a range of fingerprints belong to a unified database, based on a set of properties to the texture of image and which are extracted and analyzed using co-occurrence  matrix (Event), These properties are (contrast ,correlation, determined, homogeneity), and after extracting properties, a combination of neural networks (Cascade Neural Network CNN and Radial Basis Functions netwoek RBFN and Elman Neural Network ENN) used to distinguish fingerprint, and the results of training 100%  for the three networks after being trained on the network (18) sample where each person(3)samples.
Network efficiency was measured in recognition by using scale (training rate) and scale (recognition rate RR) for comparison between these networks to see the best network in the recognition.

Adoption of the Co-Occurrence Matrix and Artificial Neural Networks in Fingerprint Recognition

Maysoon Khidr Al-Nuaimi

AL-Rafidain Journal of Computer Sciences and Mathematics, 2013, Volume 10, Issue 1, Pages 127-136
DOI: 10.33899/csmj.2013.163446

This paper presents a new method for fingerprint recognition depending on various sizes of fingerprint images. The proposed algorithm applied on more than 30 fingerprint samples, the results was good.
The proposed algorithm begins with apply enhancement operations on the fingerprint image to eliminate unwanted noise around the fingerprint by using median filter. Then apply thinning operation on the enhanced image and compute co-occurrence matrices for produced image. Next, the properties of the co-occurrence matrices used as inputs of the neural network for recognition process. To speed the recognition process back propagation network used. The ratio of recognition  about 100%.

Fingerprint Image Pre- Post Processing Methods for Minutiae Extraction

Fayadh. M. Abed; Adnan Maroof

AL-Rafidain Journal of Computer Sciences and Mathematics, 2009, Volume 6, Issue 1, Pages 97-110
DOI: 10.33899/csmj.2009.163768

A set of reliable techniques is presented in this paper. These techniques include    enhancement and minutiae extraction that involve   the clarity of the ridge and valley structures of the input fingerprint images based on the frequency and orientation of the local ridges and thereby extracting correct minutiae.
            Fingerprint image enhancement algorithms are evaluated and implemented to understand how the enhancement algorithm works and how well it is. Two   types of features   are presented in this  job. (i) global ridge associated with central region of the fingerprint and (ii) minutiae associated with local ridge and  furrows structure.  Extraction of minutiae, involves  a series of image enhancement   such as normalization, ridge orientation estimation, filtering, thresholding, thinning and False minutiae removal. After applying  image enhancement and minutiae extraction techniques on a set of images, we took as a sample, the results was perfect. The minutiae has been removed and a results, we got was in  better condition.