https://github.com/dilippuri/aadhaar-card-ocr

Extract text information from Aadhaar Card using tesseract-ocr :sunglasses:
https://github.com/dilippuri/aadhaar-card-ocr

aadhaar ocr tesseract tesseract-ocr

Last synced: 11 days ago
JSON representation

Extract text information from Aadhaar Card using tesseract-ocr :sunglasses:

• Host: GitHub
• URL: https://github.com/dilippuri/aadhaar-card-ocr
• Owner: dilippuri
• Created: 2016-06-17T06:17:34.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2022-08-14T12:38:45.000Z (about 2 years ago)
• Last Synced: 2024-10-12T21:44:28.909Z (26 days ago)
• Topics: aadhaar, ocr, tesseract, tesseract-ocr
• Language: Python
• Homepage:
• Size: 421 KB
• Stars: 131
• Watchers: 10
• Forks: 68
• Open Issues: 7
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
This document for OCR

![Aadhaar to JSON](AadhaarCardOCR1.jpg?raw=true "Aadhaar Card image")

*****************************************************

Problem:

*****************************************************

	Extract information from image of Aadhaar Card by OCR in proper format.

		Information like - 

					Name, Year of Birth, Gender, UID

*****************************************************

Solution:

*****************************************************

	Steps:

		-> Take image

		-> crop to box(which has text in it)

		-> convert into gray scale(mono crome)

		-> give to tesseract

		-> text(output of tesseract)

	Now we will process this text means we will get meaningful information from it.

		-> find name using name database

		-> find gender

		-> find year of birth

		-> find for Aadhar ID(UID)

	for verfication please see aadhar_detail.txt file

	

*****************************************************

Dependent packages

*****************************************************

	-python

	-opencv

	-numpy

	-pytesseract

	-JSON

	-difflib

	-csv

	-PIL

	-SciPy

	-dataparser

*****************************************************

Structure and Usage

*****************************************************

	Directories:

		src-

			which contains code files		

		testcases-

			which contains testing images

		result

			it contains JSON object

			

	Usage:

		python file_name.py [input image]

		Output will be JSON object name

*****************************************************

:100: