LOCAL FEATURES FOR OFF-LINE FORENSIC SIGNATURE VERIFICATION

[1]  Song Wang,et al.  Part-based methods for handwritten digit recognition , 2013, Frontiers of Computer Science.

[2]  Robert Sablatnig,et al.  Writer Retrieval and Writer Identification Using Local Features , 2012, 2012 10th IAPR International Workshop on Document Analysis Systems.

[3]  Marcus Liwicki,et al.  Comparative Study of Part-Based Handwritten Character Recognition Methods , 2011, 2011 International Conference on Document Analysis and Recognition.

[4]  Kanghun Jeong,et al.  Object Detection Using FAST Corner Detector Based on Smartphone Platforms , 2011, 2011 First ACIS/JNU International Conference on Computers, Networks, Systems and Industrial Engineering.

[5]  Marcus Liwicki,et al.  Forensic Signature Verification Competition 4NSigComp2010 - Detection of Simulated and Disguised Signatures , 2010, 2010 12th International Conference on Frontiers in Handwriting Recognition.

[6]  Yi Zhou,et al.  SSIFT: An Improved SIFT Descriptor for Chinese Character Recognition in Complex Images , 2009, 2009 International Symposium on Computer Network and Multimedia Technology.

[7]  Robert Sablatnig,et al.  Recognition of Degraded Handwritten Characters Using Local Features , 2009, 2009 10th International Conference on Document Analysis and Recognition.

[8]  Lianwen Jin,et al.  Character-SIFT: A Novel Feature for Offline Handwritten Chinese Character Recognition , 2009, 2009 10th International Conference on Document Analysis and Recognition.

[9]  K. Pulli,et al.  SURFTrac: Efficient tracking and continuous object recognition using local feature descriptors , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[10]  Angelo Marcelli,et al.  Disguising writers identification: an experimental study , 2009 .

[11]  Giuseppe Pirlo,et al.  Automatic Signature Verification: The State of the Art , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[12]  Tom Drummond,et al.  Fusing points and lines for high performance tracking , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[13]  Samy Bengio,et al.  A comparative study of adaptation methods for speaker verification , 2002, INTERSPEECH.

[14]  Bryan Found,et al.  Forensic handwriting examiners' expertise for signature comparison. , 2002, Journal of forensic sciences.

[15]  Horst Bunke,et al.  Using a Statistical Language Model to Improve the Performance of an HMM-Based Cursive Handwriting Recognition System , 2001, Int. J. Pattern Recognit. Artif. Intell..

[16]  Sargur N. Srihari,et al.  On-Line and Off-Line Handwriting Recognition: A Comprehensive Survey , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[17]  David G. Lowe,et al.  Object recognition from local scale-invariant features , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[18]  Réjean Plamondon,et al.  Automatic signature verification and writer identification - the state of the art , 1989, Pattern Recognit..

[19]  N. Otsu A threshold selection method from gray level histograms , 1979 .