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10 th International Conference of Information System and Security

This paper discusses the problem of fake security documents and the demand for a quick and accurate authentication solution. It explores various areas of document examination and proposes an automated approach using image processing and pattern recognition. The paper also presents the current progress, future work plan, and potential applications of the proposed method.

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10 th International Conference of Information System and Security

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  1. 10th International Conference of Information System and Security 16-20 Dec 2014, IDRBT, Hyderabad Ph D Symposium Automatic Authentication of Printed Security Documents By Biswajit Halder Dept. Of Computer Science University Of Burdhwan Burdhwan, W. Bengal, India biswajithalder88@gmail.com

  2. Security Documents Security Document achieved by 4-Layer Techniques – using stock of paper, special type of ink or coating, unique no of bar-code and complex graphics respectively. High Security Documents- -Currency Note -deeds -Wills -passports Medium Security documents- -shares and bonds -Checks Low security Documents - -Lottery Tickets -Tickets -Drafts

  3. Security Category

  4. Problem and Demand • Problem – • With advent of high quality scanning and printing technology, generation of fake documents is an easy affair. • Amount of fake documents is now a serious threat to our society. • To check every document in question, asking help of forensic experts is an unrealistic solution, • Forensic experts may take time to give their views. • The frequency of such documents in question may be large Demand is – - A Quick Answer - Ability to process large number of Document - Sometimes low cost solution

  5. Present Area of Authentication Checking Generally Document Examination done on following areas – • Forgery Specialists - Analysis by public or private experts • Document examiner -Analysis through laboratory equipment • - Checking Document Dating - verification of age • - Fraud investigator - focuses on money trail and criminal intent • - Testing Paper – Generally tested by chemical methods • - Testing Ink - Generally tested by chemical methods • - Handwriting Analysts • - Typewriting Analysts

  6. Why Automation? • Speed and Accuracy check through maximum no. of features • More Useful in Electronic check image for bank-check Processing • Automatic banknote recognition with features level analysis. • Applications in Automated Teller Machines (ATM) • Stresses to be “self-defending”, rather than relying on heavy law enforcement. • Guiding design and R&D strategy

  7. Work-Area Based on Image Processing and Pattern Recognition • I. Current Progress • 1. Artwork based Authentication • a) Micro Print / fine line base module • b) Line Half-tone document image • 2. Printing Technique Identification • 3. Ink age determination • 4. Paper based Authentication • II. Future Work-Plan • 1. Enhancement of line-HT Document image • 2. Modeling of Ink-Color degradation • 3. Implementation by Currency Note verificationa) Art-work base • b) Printing technique • c) Ink base

  8. Bank- Cheques Authentication • Color Feature • Kurtosis of Image Color • Gray level Variation • Image Hue • 2) Back-Ground Artworks • Line Quality Measure • Fourier Power Spectrum • Binary Correlation

  9. Flow Chart of Bank-Cheques Authentication

  10. IHT for Line Half –Tone • - Better Visualization • - Document examination • - For reprint • - Automatic document Authentication

  11. Proposed Method • Learning based pattern classification technique - More than one NN involved - Finding lpi information

  12. Result

  13. Printing Technique Verification

  14. Result

  15. Ink-age Determination • - Pointing Absolute Document Dating • Yellowish and brownish effect on documents with its age. • Gray and color level features are extracted. • 5-decade samples are considered i.e. 30’s, 40’s, 50’s, 60’s and 70’s. • Through MLP-NN used for determination

  16. Detecting fluorescent paper pulps for Currency Note Checking Overall Approach (i) Detect pulps in a UV scanned banknote under identification and verification phase (ii) Extract features from the detected pulps (iii) Train a NN classifier based training samples that include both genuine and fake notes. (iv) Finally Test the documents by trained classifier.

  17. Enhancement of Low Frequency Line Half-tone Document Block Diagram of Proposed IHT Dot Pattern Corresponding of each quantization level

  18. Result: Enhancement of Low Frequency LHT Document Comparison analysis of Lena Eye a) HT image with different lpi b) reconstructed image c) corresponding PSNR value d) Corresponding SSIM value

  19. Modelling of Ink-Color degradation on old printed documents Role of this model – 1. Better insight about how the color change overtime. 2. Based on ACO based optimization technique 3. Prediction document condition after certain years. 4. Ink age determination Proposed model

  20. Authentication Verify by Paper Currency Note

  21. Result: Authentication of Paper Currency Note Green Line –Printing, Red Line – Ink, Blue Line – Art-Work

  22. Publication and Future Plan

  23. Future Plan • Ankush Roy, Biswaiit Halder, Utpal Garain and David Doermann. "Automatic Authentication of Banknotes." Springer, International journal of document analysis and recognition (IJDAR), (Review stage). • B. Halder, U. Garain, Rajkumar Darbar and Abhoy C. Mondal and “Inverse of Low Resolution Line Halftone Images for Document Inspection”, Springer, 6th International Workshop on Computational Forensics (IWCF 2014 , ICPR Workshop) Sweden. (Published). • B. Halder, A. C. Mondal and R. Darbar , “Enhancement of low frequency line halftone document images through inverse half toning method”, IJSISE, InderScience, (Under Preparation). • B. Halder and A. C. Mondal “Modeling of ink-color degradation on old printed documents ” IJCVR (Under Preparation). • B. Halder, and U. Garain “Microprint line Design based Authentication of Security paper documents”, Elsevier, Pattern RecognitionLetters (PRL) (Under Preparation).

  24. Acknowledgements Thank You This research work was supported and got technical help from CVPR Dept., ISI, Kolkata, India. I would like to thank my guides Dr. Utpal Garain (Asso. Prof. CVPR, ISI, Kolkata, India) and Dr. Abhoy Ch. Mondal (Asso. Professor, Dept. Of Computer Science, University Of Burdhwan, WB, India) for his guidance and important suggestions. Also, I am sincerely thank the questioned document examiners of the Central Forensic Science Laboratory (CFSL), Govt. of India for their kind help and cooperation.

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