Deep Scan

Deep Scan

Mrs.M.Manimegela#1,Kavitha K#2,Abitha M#3,Anandhi A#4,Dshanthini R#5
#1Assistant Professor, Department of Computer Science and Engineering, Sri Shakthi Institute of Engineering and Technology,

Coimbatore, TamilNadu, India. E-mail: manimegalacse@siet.ac.in

#2Student ,Department of Computer Science and Engineering, Sri Shakthi Institute of Engineering and Technology, Coimbatore, Tamil Nadu, India. E-mail: kavithak23cse@srishakthi.ac.in

#3Student ,Department of Computer Science and Engineering, Sri Shakthi Institute of Engineering and Technology, Coimbatore, Tamil Nadu, India. E-mail: abitham23cse@srishakthi.ac.in

#4Student ,Department of Computer Science and Engineering, Sri Shakthi Institute of Engineering and Technology, Coimbatore, Tamil Nadu, India. E-mail: anandhia23cse@srishakthi.ac.in

#2Student ,Department of Computer Science and Engineering, Sri Shakthi Institute of Engineering and Technology, Coimbatore, Tamil Nadu, India. E-mail: dshanthinir23cse@srishakthi.ac.in

Abstract:

ABSTRACT In today’s digital-first environment, the verification of documents has become a mission-critical task for organizations across sectors such as education, finance, law, and government. With the growing sophistication of forgery techniques, traditional methods of document validation are no longer sufficient. DeepScan is a next- generation document authentication application designed to detect and prevent the use of fake or tampered documents through the integration of advanced image processing, deep learning, and optical character recognition (OCR).The application enables users to scan physical or digital documents using a mobile device or desktop interface. Once scanned, DeepScan performs a comprehensive analysis by comparing the document against trusted templates or verified datasets. It examines elements such as fonts, spacing, alignment, official seals, signatures, and embedded metadata to detect discrepancies. OCR technology is utilized to extract and analyze textual information, while machine learning models are employed to identify subtle signs of manipulation that might escape human detection. DeepScan’s real-time processing capability ensures that users receive instant feedback on the authenticity of the document, accompanied by a detailed verification report. This significantly streamlines verification workflows for institutions that deal with high volumes of documentation, including universities, human resources departments, banks, and legal entities.The app also features modular integration with external verification APIs and government or institutional databases, allowing it to cross-reference data for added accuracy and legitimacy. Furthermore, its self-learning algorithm continuously evolves by recognizing and adapting to emerging forgery trends, thereby maintaining its effectiveness in a constantly changing threat landscape.By automating the document verification process and reducing the margin for human error, DeepScan enhances organizational security and operational efficiency. Its intuitive user interface, coupled with robust backend intelligence, makes it a reliable solution for ensuring document authenticity. DeepScan stands as a vital tool in the fight against document fraud, safeguarding trust and integrity in both digital and paper-based records.

Keywords: Document Authentication, Deep Learning, Optical Character Recognition (OCR), Image Processing, Document Verification, Forgery Detection, Real-time Analysis, Machine Learning, Metadata Analysis, Template Matching, Digital Security, Fraud Prevention, Mobile Document Scanning, Verification APIs, Automated Validation.