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The Development Of Information Technology Has Been Increasingly Changing The Means Of Information Exchange Leading To The Need Of Digitizing Print Documents. In The Present Era, There Is A Lot Of Fraud That Often Occurs. For Example, Is Account Fraud, To Avoid Account Fraud There Was Verification Using ID Card Extraction Using OCR And NLP. Optical Character Recognition (OCR) Is A Technology That Used To Generate Text From Images. With OCR We Can Extract Aadhar Card Into Text Using Pytesseract. To Improve The Accuracy We Made Text Corrections Using Natural Language Processing (NLP) Basic Tools To Fixing The Text. With 5 Aadhar Card Image, We Compared The Performance With Three Different OCR Libraries. The Result Of Our Experiment Shows That Pytesseract Had The Best Performance.The Resultant Edge Image Contains The Broken Characters. To Fill These Gaps, We Apply The Dilation Operator That Increases The Thickness Of The Characters. Dilation Fills The Broken Characters, However, Also Add Extra Thickness That Is Then Removed Through Applying The Morphological Thinning. Finally, Dilation And Thinning Are Applied In Combination To Optical Character Recognition (OCR) To Segment And Recognize The Characters Including The Name, ID, DOB, Gender And Photo Of Person.

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