An Accuracy Examination of OCR Tools
Jayesh Majumdar1, Richa Gupta2
1Jayesh Majumdar, Jaypee Institute of Information Technology, Noida, India.
2Richa Gupta, Jaypee Institute of Information Technology, Noida, India.
Manuscript received on 21 September 2019 | Revised Manuscript received on 30 September 2019 | Manuscript Published on 01 October 2019 | PP: 5-9 | Volume-8 Issue-9S4 July 2019 | Retrieval Number: I11020789S419/19©BEIESP | DOI: 10.35940/ijitee.I1102.0789S419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: 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.
Keywords: OCR tools; Orcad; GOCR; Tensorflow; Tesseract;
Scope of the Article: Image Processing and Pattern Recognition