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Optical Character Recognition using Deep Neural Network
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 176 - Number 41 |
| Year of Publication: 2020 |
| Authors: Raajkumar G., Indumathi D. |
10.5120/ijca2020920552
|
Raajkumar G., Indumathi D. . Optical Character Recognition using Deep Neural Network. International Journal of Computer Applications. 176, 41 ( Jul 2020), 61-65. DOI=10.5120/ijca2020920552
Abstract
Optical Character Recognition is a method of extracting text from image. Its main purpose is to make editable document from existing paper or image files. Optical character recognition task involves identifying simple edge detection technique and matching them with predefined patterns. It is a compartment of image recognition and is extensively used as a form of data entry with the input being some sort of printed document or data record like statements from bank, invoices, resume, business card and passport. An existing neural network (LSTM) based OCR model is able to identify text in an image but it could not able to identify the text in a tilted / rotated image. This paper aims at analyzing various text images like blurred image, tilted image and it identifies the text from these images using deep learning models.
References
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