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PYTHON OCR: SEC Digital meter Reading phase 1

The Saudi Electricity Company's project employs OCR tools like Tesseract and cloud services for text extraction from electronic component images. Despite progress in character recognition, the project's next phase aims to refine identification by implementing boundary boxes for classification, leading to data conversion into CSV format.

PYTHON OCR: SEC Digital meter Reading phase 1

The Saudi Electricity Company's project employs OCR tools like Tesseract and cloud services for text extraction from electronic component images. Despite progress in character recognition, the project's next phase aims to refine identification by implementing boundary boxes for classification, leading to data conversion into CSV format.

Team Members:

M Hamza

Advisors:

Dr. M Imran (Professor)

Affiliation:

Arid University

Tech Stack

Python

Team Members:

M Hamza

Advisors:

Dr. M Imran (Professor)

Affiliation:

Arid University

Tech Stack:

Python

Project Description:

The Saudi Electricity Company Digital Meter Reading Project's Phase I progress report focuses on Optical Character Recognition (OCR) for extracting text from images of electronic components. Utilizing tools like Tesseract and exploring cloud services like GoogleVision, AWS Textract, and Azure OCR, the project aims to overcome challenges in non-traditional OCR, particularly in detecting arbitrary text from complex documents and natural scenes. The methodology involves converting image characters to text, with the next phase dedicated to refining character identities through boundary boxes and converting the data into CSV format for further analysis.

Project Deliverables:


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