scholarly journals Improvement of the Fingerprint Recognition Process

2017 ◽  
Vol 7 (2) ◽  
pp. 1-16 ◽  
Author(s):  
Farah Dhib Tatar ◽  
Mohsen Machhout
Keyword(s):  
Fingerprint Recognition ◽  
Recognition Process

scholarly journals Multibiometric authentication with MATLAB simulation

2018 ◽  
Vol 7 (1.7) ◽  
pp. 47
Author(s):  
P Selvarani ◽  
N Malarvizhi
Keyword(s):  
Iris Recognition ◽  
Hamming Distance ◽  
Research Work ◽  
Histogram Equalization ◽  
Fingerprint Recognition ◽  
Morphological Operations ◽  
Matlab Simulation ◽  
Rubber Sheet ◽  
Recognition Process ◽  
Canny Edge

Multimodal Biometric Authentication has been used as more security purpose for establishing the user Identification, Authentication and Verification purpose. Multimodal Biometric like Fingerprint and iris are used in this research work for authentication purpose using Matlab simulation. Fingerprint recognition process like Image Enhancement, binarization, Segmentation, thinning, Minutia marking, and Matching are performed with various techniques like Histogram Equalization, Adaptive Binarization, Morphological operations, Minutiae based techniques etc.,Iris recognition process like Segmentation, Normalization, Encoding and Matching are performed with various techniques like Canny edge detection, Daughman’s Rubber sheet model, Hamming Distance etc., can be applied for Fingerprint and iris recognition for authentication purpose. Finally Performance the measure of Precision, Recall, F-Score and Accuracy has evaluated in both fingerprint and iris. It can be concluded Iris Accuracy is higher 0.96% compared with fingerprint accuracy 0.81%.

scholarly journals New Optical Methods for Liveness Detection on Fingers

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Martin Drahansky ◽  
Michal Dolezel ◽  
Jan Vana ◽  
Eva Brezinova ◽  
Jaegeol Yim ◽  
...  
Keyword(s):  
Skin Diseases ◽  
Pressure Change ◽  
Fingerprint Recognition ◽  
Optical Characteristics ◽  
Optical Methods ◽  
Detection Methods ◽  
Recognition Process ◽  
Liveness Detection ◽  
Research Activities ◽  
Finger Use

This paper is devoted to new optical methods, which are supposed to be used for liveness detection on fingers. First we describe the basics about fake finger use in fingerprint recognition process and the possibilities of liveness detection. Then we continue with introducing three new liveness detection methods, which we developed and tested in the scope of our research activities—the first one is based on measurement of the pulse, the second one on variations of optical characteristics caused by pressure change, and the last one is based on reaction of skin to illumination with different wavelengths. The last part deals with the influence of skin diseases on fingerprint recognition, especially on liveness detection.

Fluency Board Streamlines Recognition Process

ASHA Leader ◽  
2010 ◽  
Vol 15 (6) ◽  
pp. 22-23
Author(s):  
James McClure ◽  
Chamonix Olsen
Keyword(s):  
Recognition Process

Face Recognition Process A Survey

2019 ◽  
Vol 7 (6) ◽  
pp. 999-1005
Author(s):  
Kavita Lodhi ◽  
Vandan Tewari ◽  
Priyanka Bamne
Keyword(s):  
Face Recognition ◽  
Recognition Process

Analysis of Fingerprint Recognition System Using Neural Network

2020 ◽  
Author(s):  
Ganesh Awasthi ◽  
Dr. Hanumant Fadewar ◽  
Almas Siddiqui ◽  
Bharatratna P. Gaikwad
Keyword(s):  
Neural Network ◽  
Recognition System ◽  
Fingerprint Recognition

Evaluation of the effectiveness of different image skeletonization methods in biometric security systems

2020 ◽  
Vol 10 ◽  
Author(s):  
Mariya Nazarkevych ◽  
Serhii Dmytruk ◽  
Volodymyr Hrytsyk ◽  
Olha Vozna ◽  
Anzhela Kuza ◽  
...  
Keyword(s):  
Experimental Studies ◽  
Fingerprint Recognition ◽  
Good Time ◽  
Gabor Filtering ◽  
Security Systems ◽  
Thinning Algorithm ◽  
Biometric Security ◽  
Recognition Quality ◽  
Control And Management ◽  
The Internet Of Things

Background: Systems of the Internet of Things are actively implementing biometric systems. For fast and high-quality recognition in sensory biometric control and management systems, skeletonization methods are used at the stage of fingerprint recognition. The analysis of the known skeletonization methods of Zhang-Suen, Hilditch, Ateb-Gabor with the wave skeletonization method has been carried out and it shows a good time and qualitative recognition results. Methods: The methods of Zhang-Suen, Hildich and thinning algorithm based on Ateb-Gabor filtration, which form the skeletons of biometric fingerprint images, are considered. The proposed thinning algorithm based on Ateb-Gabor filtration showed better efficiency because it is based on the best type of filtering, which is both a combination of the classic Gabor function and the harmonic Ateb function. The combination of this type of filtration makes it possible to more accurately form the surroundings where the skeleton is formed. Results: Along with the known ones, a new Ateb-Gabor filtering algorithm with the wave skeletonization method has been developed, the recognition results of which have better quality, which allows to increase the recognition quality from 3 to 10%. Conclusion: The Zhang-Suen algorithm is a 2-way algorithm, so for each iteration, it performs two sets of checks during which pixels are removed from the image. Zhang-Suen's algorithm works on a plot of black pixels with eight neighbors. This means that the pixels found along the edges of the image are not analyzed. Hilditch thinning algorithm occurs in several passages, where the algorithm checks all pixels and decides whether to replace a pixel from black to white if certain conditions are satisfied. This Ateb-Gabor filtering will provide better performance, as it allows to obtain more hollow shapes, organize a larger range of curves. Numerous experimental studies confirm the effectiveness of the proposed method.

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