Invariant Image Recognition by Zernike Moments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fundamentals of speech recognition
Fundamentals of speech recognition
Character image enhancement by selective region-growing
Pattern Recognition Letters
Wavelet-based off-line handwritten signature verification
Computer Vision and Image Understanding
Off-Line Signature Verification: Recent Advances and Perspectives
BSDIA '97 Proceedings of the First Brazilian Symposium on Advances in Document Image Analysis
Learning Strategies and Classification Methods for Off-Line Signature Verification
IWFHR '04 Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition
On-line signature authentication using Zernike moments
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
Off-line signature recognition using morphological pixel variance analysis
Proceedings of the International Conference and Workshop on Emerging Trends in Technology
Techniques for static handwriting trajectory recovery: a survey
DAS '10 Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
An approach for on-line signature authentication using Zernike moments
Pattern Recognition Letters
A writer-independent off-line signature verification system based on signature morphology
Proceedings of the First International Conference on Intelligent Interactive Technologies and Multimedia
Off-line signature verification systems: a survey
Proceedings of the International Conference & Workshop on Emerging Trends in Technology
Offline signature verification and identification by hybrid features and Support Vector Machine
International Journal of Artificial Intelligence and Soft Computing
Writer-independent off-line signature verification using surroundedness feature
Pattern Recognition Letters
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An approach to off-line signature verification, one with an on-line flavor, is described. A sequence of data is obtained by tracing the exterior contour of the signature which allows the application of string-matching algorithms. The upper and lower contours of the signature are first determined by ignoring small gaps between signature components. The contours are combined into a single sequence so as to define a pseudo-writing path. To match two signatures a non-linear normalization method, viz., dynamic time warping, is applied to segment them into curves. Shape descriptors based on Zernike moments are extracted as features from each segment. A harmonic distance is used for measuring signature similarity. Performance is significantly better than that of a word-shape based signature verification method. When the two methods are combined, the overall performance is significantly better than either method alone. With a database of 1320 genuines and 1320 forgeries the combination method has an accuracy of 95% (with 20% rejection) which is comparable to that of on-line systems.