Vehicle License Plate Localization based on Local Binary Pattern Features

Autor:	Ascar Davix. X, Adline N Titus, Ashwina. A
Rok vydání:	2019
Předmět:	Low contrast Computer science Feature (computer vision) business.industry Local binary patterns Adaboost classifier Pattern recognition Artificial intelligence Detection rate business Intelligent transportation system License Task (project management)
Zdroj:	2019 International Conference on Recent Advances in Energy-efficient Computing and Communication (ICRAECC).
DOI:	10.1109/icraecc43874.2019.8994964
Popis:	The importance of Intelligent Transportation System (ITS) is increasing because of increasing the number of vehicles on the roads. Automatic License Plate Detection (ALPD) is still a challenging task based on weather, occlusion, dirty License Plates (LP) and some other factors. In this paper Local Binary Pattern (LBP) feature is proposed for the detection of LP region. Cascaded Adaboost classifier is used for the classification of candidate region. The input images are chosen with different conditions such as occlusion, low contrast, dirty LP images and poor illumination. The proposed technique is tested on 600 images. This method achieves 96.8% detection rate.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::ae3badd668849714079a798044fefd4d https://doi.org/10.1109/icraecc43874.2019.8994964 Zobrazit plný text záznamu