Matches in SemOpenAlex for { <https://semopenalex.org/work/W2979428650> ?p ?o ?g. }
Showing items 1 to 77 of
77
with 100 items per page.
- W2979428650 abstract "Automatic license plate recognition (ALPR) is a process of identification of the license plate from an image taken at any signal stop or parking station. The Identified information or the number plate can be used for keeping a check on signal stops or for monetary settlements at parking lots or toll stations. It can also be used around the world for law and administrative works like checking a vehicle if it is registered or not. It also finds its use in safety supervision system. The ALPR can be used upon various types of pictures like color images, black and white images and etc. ALPR may fail a number of times if the quality of the picture is not up to the mark. So, ALPR depend a lot in the image quality, and hence the challenges in its real-life application. It may be used both indoors and outdoors but it must be able to process the images both quickly and successfully in all sorts of environments, be it daytime or night time, sunny or rainy. Our proposed method mainly has three modules: 1) Detection of license plate 2) Segmentation of Characters 3) Text Box Generation. The number plates sometimes may be unclear for the cameras. It may sometimes have dirt and scratches on it and thus increasing the complexities of the ALPR system. Today nationwide ALPR has been adopted by several law and governmental agencies for its efficiency and usefulness. Public safety agencies are using the ALPR system to gather and store relevant information about people and to keep a check on the vehicular activities. It is becoming a significant tool for the Law Enforcement Agencies." @default.
- W2979428650 created "2019-10-18" @default.
- W2979428650 creator A5010780009 @default.
- W2979428650 creator A5024252440 @default.
- W2979428650 creator A5040620407 @default.
- W2979428650 creator A5084106026 @default.
- W2979428650 creator A5084191187 @default.
- W2979428650 creator A5090387999 @default.
- W2979428650 date "2019-03-01" @default.
- W2979428650 modified "2023-09-25" @default.
- W2979428650 title "An Adaptive Technique for Computer Vision Based Vehicles License Plate Detection System" @default.
- W2979428650 cites W2138049212 @default.
- W2979428650 doi "https://doi.org/10.1109/optronix.2019.8862406" @default.
- W2979428650 hasPublicationYear "2019" @default.
- W2979428650 type Work @default.
- W2979428650 sameAs 2979428650 @default.
- W2979428650 citedByCount "9" @default.
- W2979428650 countsByYear W29794286502020 @default.
- W2979428650 countsByYear W29794286502021 @default.
- W2979428650 countsByYear W29794286502022 @default.
- W2979428650 countsByYear W29794286502023 @default.
- W2979428650 crossrefType "proceedings-article" @default.
- W2979428650 hasAuthorship W2979428650A5010780009 @default.
- W2979428650 hasAuthorship W2979428650A5024252440 @default.
- W2979428650 hasAuthorship W2979428650A5040620407 @default.
- W2979428650 hasAuthorship W2979428650A5084106026 @default.
- W2979428650 hasAuthorship W2979428650A5084191187 @default.
- W2979428650 hasAuthorship W2979428650A5090387999 @default.
- W2979428650 hasConcept C111472728 @default.
- W2979428650 hasConcept C111919701 @default.
- W2979428650 hasConcept C127413603 @default.
- W2979428650 hasConcept C138885662 @default.
- W2979428650 hasConcept C154945302 @default.
- W2979428650 hasConcept C22212356 @default.
- W2979428650 hasConcept C2778582501 @default.
- W2979428650 hasConcept C2779530757 @default.
- W2979428650 hasConcept C2780560020 @default.
- W2979428650 hasConcept C31972630 @default.
- W2979428650 hasConcept C38652104 @default.
- W2979428650 hasConcept C41008148 @default.
- W2979428650 hasConcept C47796450 @default.
- W2979428650 hasConcept C78519656 @default.
- W2979428650 hasConcept C89600930 @default.
- W2979428650 hasConcept C98045186 @default.
- W2979428650 hasConceptScore W2979428650C111472728 @default.
- W2979428650 hasConceptScore W2979428650C111919701 @default.
- W2979428650 hasConceptScore W2979428650C127413603 @default.
- W2979428650 hasConceptScore W2979428650C138885662 @default.
- W2979428650 hasConceptScore W2979428650C154945302 @default.
- W2979428650 hasConceptScore W2979428650C22212356 @default.
- W2979428650 hasConceptScore W2979428650C2778582501 @default.
- W2979428650 hasConceptScore W2979428650C2779530757 @default.
- W2979428650 hasConceptScore W2979428650C2780560020 @default.
- W2979428650 hasConceptScore W2979428650C31972630 @default.
- W2979428650 hasConceptScore W2979428650C38652104 @default.
- W2979428650 hasConceptScore W2979428650C41008148 @default.
- W2979428650 hasConceptScore W2979428650C47796450 @default.
- W2979428650 hasConceptScore W2979428650C78519656 @default.
- W2979428650 hasConceptScore W2979428650C89600930 @default.
- W2979428650 hasConceptScore W2979428650C98045186 @default.
- W2979428650 hasLocation W29794286501 @default.
- W2979428650 hasOpenAccess W2979428650 @default.
- W2979428650 hasPrimaryLocation W29794286501 @default.
- W2979428650 hasRelatedWork W1669643531 @default.
- W2979428650 hasRelatedWork W2005437358 @default.
- W2979428650 hasRelatedWork W2008656436 @default.
- W2979428650 hasRelatedWork W2023558673 @default.
- W2979428650 hasRelatedWork W2039154422 @default.
- W2979428650 hasRelatedWork W2110230079 @default.
- W2979428650 hasRelatedWork W2122581818 @default.
- W2979428650 hasRelatedWork W2134924024 @default.
- W2979428650 hasRelatedWork W2517104666 @default.
- W2979428650 hasRelatedWork W2182382398 @default.
- W2979428650 isParatext "false" @default.
- W2979428650 isRetracted "false" @default.
- W2979428650 magId "2979428650" @default.
- W2979428650 workType "article" @default.