LOCAL DIFFERENCE THRESHOLD LEARNING IN FILTERING NORMAL WHITE NOISE
The article was aimed at studying the process of learning by the local difference threshold when filtering normal white noise. The existing learning algorithms for image processing were analyzed and their advantages and disadvantages were identified. The influence of normal white noise on the recog...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Lublin University of Technology
2023-06-01
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| Series: | Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska |
| Subjects: | |
| Online Access: | https://ph.pollub.pl/index.php/iapgos/article/view/3664 |
| _version_ | 1827912342598320128 |
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| author | Leonid Timchenko Natalia Kokriatskaia Volodymyr Tverdomed Natalia Kalashnik Iryna Shvarts Vladyslav Plisenko Dmytro Zhuk Saule Kumargazhanova |
| author_facet | Leonid Timchenko Natalia Kokriatskaia Volodymyr Tverdomed Natalia Kalashnik Iryna Shvarts Vladyslav Plisenko Dmytro Zhuk Saule Kumargazhanova |
| author_sort | Leonid Timchenko |
| collection | DOAJ |
| description |
The article was aimed at studying the process of learning by the local difference threshold when filtering normal white noise. The existing learning algorithms for image processing were analyzed and their advantages and disadvantages were identified. The influence of normal white noise on the recognition process is considered. A method for organizing the learning process of the correlator with image preprocessing by the GQP method has been developed. The dependence of the average value of readings of the rank CCF (RCCF) of GQPs of the reference and current images, representing realizations of normal white noise, on the probability of formation of readings of zero GQP is determined. Two versions of the learning algorithm according to the described learning method are proposed. A technique for determining the algorithm efficiency estimate is proposed.
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| first_indexed | 2024-03-13T02:14:33Z |
| format | Article |
| id | doaj.art-f1aa2f2046ab4a49ad40c867f099770c |
| institution | Directory Open Access Journal |
| issn | 2083-0157 2391-6761 |
| language | English |
| last_indexed | 2024-03-13T02:14:33Z |
| publishDate | 2023-06-01 |
| publisher | Lublin University of Technology |
| record_format | Article |
| series | Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska |
| spelling | doaj.art-f1aa2f2046ab4a49ad40c867f099770c2023-06-30T19:08:25ZengLublin University of TechnologyInformatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska2083-01572391-67612023-06-0113210.35784/iapgos.3664LOCAL DIFFERENCE THRESHOLD LEARNING IN FILTERING NORMAL WHITE NOISELeonid Timchenko0Natalia Kokriatskaia1Volodymyr Tverdomed2Natalia Kalashnik3Iryna Shvarts4Vladyslav Plisenko5Dmytro Zhuk6Saule Kumargazhanova7State University of Infrastructure and Technology, Kyiv, UkraineState University of Infrastructure and Technology, Kyiv, UkraineState University of Infrastructure and Technology, Kyiv, UkraineNational Pirogov Memorial Medical University, Vinnytsia, UkraineVinnytsia National Technical University, Vinnytsia, UkraineState University of Infrastructure and Technology, Kyiv, UkraineState University of Infrastructure and Technology, Kyiv, UkraineD.Serikbayev East Kazakhstan State Technical University, Ust-Kamenogorsk, Kazakhstan The article was aimed at studying the process of learning by the local difference threshold when filtering normal white noise. The existing learning algorithms for image processing were analyzed and their advantages and disadvantages were identified. The influence of normal white noise on the recognition process is considered. A method for organizing the learning process of the correlator with image preprocessing by the GQP method has been developed. The dependence of the average value of readings of the rank CCF (RCCF) of GQPs of the reference and current images, representing realizations of normal white noise, on the probability of formation of readings of zero GQP is determined. Two versions of the learning algorithm according to the described learning method are proposed. A technique for determining the algorithm efficiency estimate is proposed. https://ph.pollub.pl/index.php/iapgos/article/view/3664traininglocal difference thresholdfiltering normal white noise |
| spellingShingle | Leonid Timchenko Natalia Kokriatskaia Volodymyr Tverdomed Natalia Kalashnik Iryna Shvarts Vladyslav Plisenko Dmytro Zhuk Saule Kumargazhanova LOCAL DIFFERENCE THRESHOLD LEARNING IN FILTERING NORMAL WHITE NOISE Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska training local difference threshold filtering normal white noise |
| title | LOCAL DIFFERENCE THRESHOLD LEARNING IN FILTERING NORMAL WHITE NOISE |
| title_full | LOCAL DIFFERENCE THRESHOLD LEARNING IN FILTERING NORMAL WHITE NOISE |
| title_fullStr | LOCAL DIFFERENCE THRESHOLD LEARNING IN FILTERING NORMAL WHITE NOISE |
| title_full_unstemmed | LOCAL DIFFERENCE THRESHOLD LEARNING IN FILTERING NORMAL WHITE NOISE |
| title_short | LOCAL DIFFERENCE THRESHOLD LEARNING IN FILTERING NORMAL WHITE NOISE |
| title_sort | local difference threshold learning in filtering normal white noise |
| topic | training local difference threshold filtering normal white noise |
| url | https://ph.pollub.pl/index.php/iapgos/article/view/3664 |
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