Статья

Evaluation of the Effectiveness of Different Image Skeletonization Methods in Biometric Security Systems

Mariya NazarkevychDepartment of Publishing Information Technologies, Institute of Computer Science and Information Technologies, Lviv Polytechnic National University, Lviv, UkraineSerhii DmytrukDepartment of Publishing Information Technologies, Institute of Computer Science and Information Technologies, Lviv Polytechnic National University, Lviv, UkraineVolodymyr HrytsykDepartment of Automated Control Systems, Institute of Computer Science and Information Technologies, Lviv Polytechnic National University, Lviv, UkraineO. Ye. VoznaDepartment of Biological and General Chemistry, Faculty of Food Technologies and Biotechnology, Stepan Gzhytskyi National University of Veterinary Medicine and Biotechnologies Lviv, Lviv, UkraineAnzhela KuzaDepartment of Humanities Education, Faculty of Civil Engineering and Architecture, Lviv National Agrarian University, Lviv, UkraineOleksii ShevchukDepartment of Automation and Computer Technologies, Faculty of Computer Graphic Engineering, Ukrainian Academy of Printing, Lviv, UkraineYaroslav VoznyiDepartment of Publishing Information Technologies, Institute of Computer Science and Information Technologies, Lviv Polytechnic National University, Lviv, UkraineIryna MaslanychDepartment of Applied Linguistics, Institute of Computer Science and Information Technologies, Lviv Polytechnic National University, Lviv, UkraineVasyl SheketaDepartment of Software Engineering, Institute of Information Technologies, Ivano-Frankivsk National Technical University of Oil and Gas, Ivano-Frankivsk, Ukraine

2020en

ABI

Аннотация

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 a 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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Идентификаторы

DOI: 10.2174/2210327910666201210151809

Цитирования и источники

Цитирований: 2Использованных источников: 0

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