Vehicular number plate recognition (VNPR) is an important issue which can be solved using image processing and computer vision. VNPR process, when taken into consideration, can be used to solve a variety of issues in the fields of road safety and security. The problems can range from parking concerns to traffic control and might also include situations related to tollbooth or speed limit issues. Vehicle number plate recognition has a lot of side complexities arising due to a lot of factors including variable light dissipation, camera quality, and also speed at which the vehicle is moving. The proposed system will be able to identify number plates of cars and bikes and help trace the owner of that vehicle. We use various machine learning techniques and image processing utilities along with computer vision to address few of the issues which can be solved using the same.
Automatic Vehicular Number Plate Recognition (VNPR) for Identification of Vehicle Using OCR and Tesseract
Lect. Notes in Networks, Syst.
03.04.2020
9 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Machine learning , Vehicular number plate recognition (VNPR) , Artificial neural network (ANN) , Image processing , Optical character recognition (OCR) , Computer vision , K-nearest neighbor Artificial Intelligence , Electronics and Microelectronics, Instrumentation , Power Electronics, Electrical Machines and Networks , Engineering , Communications Engineering, Networks
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