Open AccessAn Accuracy Examination of OCR Tools
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.i1102.0789s419
Subject(s) - optical character recognition , computer science , artificial intelligence , character (mathematics) , image processing , reading (process) , segmentation , orientation (vector space) , pattern recognition (psychology) , optical flow , computer vision , natural language processing , document processing , image (mathematics) , mathematics , linguistics , geometry , philosophy
In this research paper, the authors have aimed to do a comparative study of optical character recognition using different open source OCR tools. Optical character recognition (OCR) method has been used in extracting the text from images. OCR has various applications which include extracting text from any document or image or involves just for reading and processing the text available in digital form. The accuracy of OCR can be dependent on text segmentation and pre-processing algorithms. Sometimes it is difficult to retrieve text from the image because of different size, style, orientation, a complex background of image etc. From vehicle number plate the authors tried to extract vehicle number by using various OCR tools like Tesseract, GOCR, Ocrad and Tensor flow. The authors in this research paper have tried to diagnose the best possible method for optical character recognition and have provided with a comparative analysis of their accuracy