Detection of regularities in the parameters of the atebgabor method for biometric image filtration
Journal Title: Восточно-Европейский журнал передовых технологий - Year 2019, Vol 1, Issue 2
Abstract
<p>The study has developed a new image filtering method based on Ateb-Gabor. The method involves the well-known Gabor filter that helps convert images with clear contours. Therefore, this method is applicable to biometric images where the creation of clear contours is particularly relevant. During Gabor filtration, the image is transformed by multiplying the harmonic function by the Gaussian function. Ateb-functions are a generalization of elementary trigonometry and, accordingly, have greater functionality for known harmonic functions.</p><p>Ateb-Gabor filtering makes it possible to change the intensity of the whole image as well as intensity in certain ranges and thus gives more contrast to certain areas of an image. Ateb-functions are changed by two rational parameters, and this provides flexible control of the filtering. Research has been made on the properties of Ateb-functions as well as the possibility of changing the amplitude and the frequency of alternations when filtering by the Ateb-Gabor. The development of filtration is based on a two-dimensional Ateb-Gabor; its dependencies have been analyzed and appropriate experiments have been performed. The relationship between the frequency and the width of the Ateb-Gabor filter has been determined, which has made it possible to produce filters for finding edges of objects with different frequencies and sizes.</p><p>Appropriate software has been developed for python filtering without the use of third-party libraries that are associated with image processing. Fingerprints were filtered using the developed Ateb-Gabor filter. The effectiveness of its use is shown to consist in forming more combinations of processed images. The results of numerous experiments demonstrate a successful selection of edges in an image based on the parameters of the Ateb-Gabor filter.</p>
Authors and Affiliations
Mariya Nazarkevych, Oleg Riznyk, Volodymyr Samotyy, Ulyana Dzelendzyak
Keywords
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- EP ID EP666166
- DOI 10.15587/1729-4061.2019.154862
- Views 72
- Downloads 0
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