Signature Verification

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Preprocessing• For online signatures no segmentation needs to beperformed– All parts of the signature are known after sensing• Attempt to eliminate noise from the capturing device,speed of writing, and the writing itself• Minimize the potential of eliminating writerdependencies• Solutions1) Size Normalization2) Position Normalization3) Smoothing4) Re-sampling5) Ligature
Page 5: • On-Line:Azimuth (0°-359°)Alti
Page 8: • Disadvantages:- High intra-clas
Page 11: • Acquisition devices:AlAzPYX0 10
Page 15 and 16: Resample• In order to compare two
Page 17 and 18: Smoothing• A one dimensionalGauss
Page 19 and 20: Critical Points• Def: points that
Page 21 and 22: Preprocessing Steps• Original•
Page 23 and 24: Preprocessing Steps• Coarse re-sa
Page 25 and 26: Functional vs. Parametric• Functi
Page 27 and 28: Local Features• δx and δy for p
Page 29 and 30: Temporal Features• Absolute and r
Page 31 and 32: Pattern Recognition System
Page 33 and 34: DTW Example• Match strings ‘abc
Page 35 and 36: User Dependent Normalization• Tra
Page 37 and 38: PCA• Project the distance vector
Page 39 and 40: SVC ExamplesGenuineImposter
Page 41 and 42: Pattern Recognition System
Page 43 and 44: Score FusionGlobal FeaturesLocal Fe
Page 45: Biometric Comparison

Signature Verification

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