Wyniki wyszukiwania - BazTech

1

Wybrane metody rozpoznawania osób na podstawie odcisków palców

Grad Leszek

Przegląd Teleinformatyczny

|

2020

|

T. 8, Nr 1-4 (26)

59--74

PL

W artykule przedstawiono zagadnienie rozpoznawania tożsamości osób na podstawie odcisków palców. Przedstawiono aktualny stan wiedzy, wybrane metody i techniki zarówno opisu obrazu linii papilarnych, jak i metody klasyfikacji.

EN

The paper considers the issue of the identity recognition of persons on the basis of fingerprints. The current state of knowledge, selected methods and techniques of fingerprint image description and classification methods are presented.

2

Weighted multimodal biometric recognition algorithm based on histogram of contourlet oriented gradient feature description

Zhang Xinman, Cheng Dongxu, Xu Xuebin

Annals of Computer Science and Information Systems

|

2019

|

Vol. 18

381–-384

EN

Although the unimodal biometric recognition (such as face and palmprint) has higher convenience, its security is also relatively weak. The recognition accuracy is easy affected by many factors such as ambient light and recognition distance etc. To address this issue, we present a weighted multimodal biometric recognition algorithm with face and palmprint based on histogram of contourlet oriented gradient (HCOG) feature description. We employ the nonsubsampled contour transform (NSCT) to decompose the face and palmprint images, and the HOG method is adopted to extract the feature, which is named as HCOG feature. Then the dimension reduction process is applied on the HCOG feature and a novel weight value computation method is proposed to accomplish the multimodal biometric fusion recognition. Extensive experiments illustrate that our proposed weighted fusion recognition can achieve excellent recognition accuracy rates and outmatches the unimodal biometric recognition methods.

3

Palmprint recognition based on convolutional neural network-Alexnet

Gong Weiyong, Zhang Xinman, Deng Bohua, Xu Xuebin

Annals of Computer Science and Information Systems

|

2019

|

Vol. 18

313–-316

EN

In the classic algorithm, palmprint recognition requires extraction of palmprint features before classification and recognition, which will affect the recognition rate. To solve this problem, this paper uses the convolutional neural network (CNN) structure Alexnet to realize palmprint recognition. First, according to the characteristics of the geometric shape of palmprint, the ROI area of palmprint was cut out. Then the ROI area after processing is taken as input layer of convolutional neural network. Next the PRelu activation function is used to train the network to select the best learning rate and super parameters. Finally, the palmprint was classified and identified. The method was applied to PolyU Multi-Spectral Palmprint Image Database and PolyU 2D+3D Palmprint Database, and the recognition rate of a single spectrum was up to 99.99%.

4

Gradient based fingerprint orientation field estimation

Wieclaw L.

Journal of Medical Informatics & Technologies

|

2013

|

Vol. 22

203--207

EN

Accurate estimation of ridge orientation is a critical step in image preprocessing methods used in automatic fingerprint identification systems (AFIS). Fingerprint orientation plays important roles in fingerprint enhancement, classification and recognition. The most popular is gradient-based method. This paper reviews the algorithm parameters, determining the compromise between accuracy in high-curvature areas and robustness against noise.

5

The pixel alignment based algorithm for continuous orientation field estimation

Więcław Ł., Porwik P.

Journal of Medical Informatics & Technologies

|

2010

|

Vol. 15

47--52

EN

This paper presents a new estimation method of fingerprint orientation field. An accurate estimation of fingerprint orientation fields is an essential step in automatic fingerprint recognition systems (AFIS). Most popular, gradient-based method is very sensitive to noise (image quality). Proposed algorithm is a modification of, more resistant to noise, mask-based method, which provides orientation limited to discrete values. This modification is based on aggregation of pixel values differentiation and was used to more precise estimation of magnitude of orientation vectors. This approach allows to obtain a continuous values of orientation field still maintaining robust to noise.