Improve OCR Accuracy with Advanced Image Preprocessing using Machine Learning with Python
Sanjeev Kumar1, Mahika Sharma2, Kritika Handa3, Rishika Jaiswal4
1Kritika Handa*, Computer Science And Engineering Department, ABES Institute Of Technology, Ghaziabad, India.
2Mahika Sharma, Computer Science And Engineering Department, ABES Institute Of Technology, Ghaziabad, India.
3Rishika Jaiswal, Computer Science And Engineering Department, ABES Institute Of Technology, Ghaziabad, India.
4Prof. Sanjeev Kumar, Computer Science And Engineering Department, ABES Institute Of Technology, Ghaziabad, India.
Manuscript received on April 20, 2020. | Revised Manuscript received on May 05, 2020. | Manuscript published on May 10, 2020. | PP: 1026-1030 | Volume-9 Issue-7, May 2020. | Retrieval Number: G5745059720/2020©BEIESP | DOI: 10.35940/ijitee.G5745.059720
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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: Optical Character Recognition or Optical Character Reader (OCR) is a pattern-based method consciousness that transforms the concept of electronic conversion of images of handwritten text or printed text in a text compiled. Equipment or tools used for that purpose are cameras and apartment scanners. Handwritten text is scanned using a scanner. The image of the scrutinized document is processed using the program. Identification of manuscripts is difficult compared to other western language texts. In our proposed work we will accept the challenge of identifying letters and letters and working to achieve the same. Image Preprocessing techniques can effectively improve the accuracy of an OCR engine. The goal is to design and implement a machine with a learning machine and Python that is best to work with more accurate than OCR’s pre-built machines with unique technologies such as MatLab, Artificial Intelligence, Neural networks, etc.
Keywords: Recognition text, OCR image analysis
Scope of the Article: Machine Learning