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Ph D Symposium
Automatic Authentication of Printed Security Documents
ByBiswajit Halder
Dept. Of Computer ScienceUniversity Of Burdhwan
Burdhwan, W. Bengal, [email protected]
10th International Conference of Information System and Security
16-20 Dec 2014, IDRBT, Hyderabad
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
Security Documents
Low Medium High
Overt -See-through register -Shadow image -Unique identifier -Watermark
-Bearer ’s signature -Digital facial image -See-through register -Shadow image -Unique identifier -Watermark
-Diffractive optically-Bearer’s signature-Digital facial image -See-through register -Shadow image -Unique identifier -Watermark
Semi- Covert
-High resolution printing processes -Security-type printing features
-High resolution printing processes -Security-type printing features
-High resolution printing processes -Security-type printing features
Covert -Security fibre paper-Screen angle
modulation
-Security fibre paper-Hidden image -Screen angle modulation -Security ink
-Security fibre paper-Hidden image -Screen angle modulation -Security ink -Security threads
Security Category
Problem and Demand
Demand is –- A Quick Answer- Ability to process large number of Document- Sometimes low cost solution
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
Generally Document Examination done on following areas –
Present Area of Authentication Checking
-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
• 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
Why Automation?
Based on Image Processing and Pattern Recognition
Work-Area
I. Current Progress1. Artwork based Authentication
a) Micro Print / fine line base module b) Line Half-tone document image
2. Printing Technique Identification3. Ink age determination4. Paper based Authentication
II. Future Work-Plan1. Enhancement of line-HT Document image2. Modeling of Ink-Color degradation
3. Implementation by Currency Note verification a) Art-work baseb) Printing techniquec) Ink base
Bank- Cheques Authentication
1) Color FeatureKurtosis of Image ColorGray level VariationImage Hue
2) Back-Ground ArtworksLine Quality MeasureFourier Power Spectrum Binary Correlation
Flow Chart of Bank-Cheques Authentication
Classification K-mean NN SVM
Poly RBF
Test 88.7% 97.5% 99.5% 98.5%
- Better Visualization
- Document examination
- For reprint
- Automatic document Authentication
IHT for Line Half –Tone
- Learning based pattern classification technique- More than one NN involved- Finding lpi information
Proposed Method
m 3X3 5X5 7X7
LPI K PSNR SSIM PSNR SSIM PSNR SSIM
4 24.88 0.870 26.77 0.88 28.705 0.89
70 8 25 0.87 26.87 0.87 27.69 0.87
16 24.93 0.75 27.07 0.89 29.67 0.90
Result
Printing Technique Verification
Gray Level Dominant Intensity(f1)Key Tone (f5)Hole Count(f2)
Structural Edge Roughness(f7)Area Differences (f8)Correlation Coefficient (f9)
Color Contrast (f4)Avg. Hue (f3)Avg. Color (f6)
Classification K-mean NN SVM
Poly RBF
Test 92.7% 99.5% 99.9% 99.6
Result
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
Dated as 30's 40's 50's 60's 70's
Samples
30’s 25 5 6 2 2
40’s 5 27 5 3
50’s 1 4 31 4
60’s 3 32 5
70’s 6 34
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.
Enhancement of Low Frequency Line Half-tone Document
Block Diagram of Proposed IHT
Dot Pattern Corresponding of each quantization level
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
Modelling of Ink-Color degradation on old printed documents
Proposed model
Role of this model –1. Better insight about how the color change overtime.2. Based on ACO based optimization technique3. Prediction document condition after certain years.4. Ink age determination
Authentication Verify by Paper Currency Note
INK Art-Work Printing
ANN SVM ANN SVM ANN SVM
Poly RBF Poly RBF Poly RBF
Avg. 98.5% 99.5% 94.5% 99.3% 99.3% 99% 99.8% 100 99.75%
Result: Authentication of Paper Currency Note
Green Line –Printing, Red Line – Ink, Blue Line – Art-Work
Publication and Future Plan
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 Recognition Letters (PRL) (Under Preparation).
Acknowledgements
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.
Thank You