Open AccessAUTOMATIC NUMBER PLATE RECOGNITION FOR DIFFERENT FONTS AND NON-ROMAN SCRIPT
Author(s) -
Kirad Varad Vinay,
Indla Omkar Balaobaiah,
Mujawar Sohail Mahiboob,
Shinde Dinesh Nagnath,
Darshana Patil
Publication year - 2021
Publication title -
international journal of engineering applied science and technology
Language(s) - English
Resource type - Journals
ISSN - 2455-2143
DOI - 10.33564/ijeast.2021.v05i11.052
Subject(s) - optical character recognition , artificial intelligence , computer science , computer vision , character (mathematics) , font , image processing , segmentation , character recognition , image quality , quality (philosophy) , image (mathematics) , pattern recognition (psychology) , mathematics , philosophy , geometry , epistemology
According to survey taken the total number ofvehicles in [1] India were 260 million. Therefore, there is aneed to develop Automatic Number Plate Recognition(ANPR) systems [1] in India because of the large number ofvehicles travelling on the roads. [1] It would also help inproper tracking of the vehicles, traffic examining, findingstolen vehicles, supervising parking toll and imposing strictactions against red light breaching. Automatic numberplate recognition is image processing technique for findingnumber plate from image and extracting characters fromdetected number plate. ANPR in India has always beenchallenging due to different lighting conditions, changes infonts, shapes, angles, letters size, number of lines andpadding between lines, different languages used. In ourproject we proposed a model that can detects number platewith considering all irregularities. this system usesComputer vision and machine learning technology in orderto detect number plate from image. In our proposed systemnumber plate can be of different fonts and non-romanscript. For identification of characters from number platewe use OCR (Optical character recognition) technique.OCR involves two parts: Character segmentation andCharacter Recognition. This OCR system can be used toextract characters of different fonts and non-roman script.The Quality of OCR depends on the quality of image, imagecontrast, text font style and size. To improve quality of OCRwe can use image processing technique to enhance qualityof image.