Application of Convolutional Neural Networks for Automatic Number Plate Recognition on Complex Background Images
| Parent link: | Applied Mechanics and Materials: Scientific Journal Vol. 756 : Mechanical Engineering, Automation and Control Systems (MEACS2014).— 2015.— [P. 695-703] |
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| מחבר תאגידי: | |
| מחברים אחרים: | , |
| סיכום: | Title screen The relevance of this study is stipulated by the necessity of designing techniques, algorithms, and programs improving the efficiency of automatic number plate recognition (ANPR) on images with complex backgrounds.Purpose: The aim of this work is to improve the efficiency of automatic number plate recognition on images with complex backgrounds using methods, algorithms, and programs invariant to affine and projective transformations.Design/methodology: Such techniques as artificial intelligence, pattern identification and recognition, the theory of artificial neural networks (ANN), convolutional neural networks (CNN), evolutionary algorithms, mathematical modeling, the probability theory and mathematical statistics were applied via Visual Studio and MatLab software.Findings: The software is developed allowing the automatic number plate recognition on complex background images. The convolutional neural network comprising seven layers is suggested to identify the plate localization, i.e. finding and isolating the plate on the picture. The pixel intensity histogram-based algorithm was used for character segmentation or finding individual characters on the plates. The convolutional neural network comprising six layers is designed to recognize characters. The suggested software system allows automatic number plate recognition at large angles of inclinations and rather a high speed. Режим доступа: по договору с организацией-держателем ресурса |
| שפה: | אנגלית |
| יצא לאור: |
2015
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| סדרה: | Image and Signal Processing, Recognition, Information Processing and Applied Technologies |
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| גישה מקוונת: | http://dx.doi.org/10.4028/www.scientific.net/AMM.756.695 |
| פורמט: | אלקטרוני Book Chapter |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=641421 |