Automatic Signature Extraction From Images
User authentication is required at every step in today’s technologies and security standards. Biometrics such as fingerprints, iris scans, voice recordings, and handwritten signatures are used to authenticate and verify users. Many approaches for the extraction of information and authentication have been proposed as a result of developments in automated user verification and authentication.
Handwritten signatures are the most widely accepted and used biometric trait. Paper document examination is used in forensic science to determine whether a document is authentic or not, to expose forgery, or to reveal adjustments such as additions or deletions. A piece of paper bearing handwriting or mechanically produced text or signatures, such as invoices, a counterfeit cheque, or a business contract, may be among the papers in dispute.
The bulk of signature verification and writer identification methods disclosed presume that signatures are pre-segmented and that the system receives these pre-extracted signatures directly. Additionally, the publicly accessible signature databases include pre-segmented handwritten signatures from the documents for verification.
Signature Extraction
Signatures on documents like bank cheques, invoices, wills, letters, and contracts of business are usually written in the real world when they overlap the other information contained in the document, such as texts, lines, stamps, or graphics. In such instances, applying standard image processing algorithms to extract signature pixels from these overlapping regions becomes extremely difficult. It is required to segment signatures out of the document to get effective results using state-of-the-art signature verification technologies.
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