ICDAR2013 - Competition on Stroke Recovery from Offline Data


The detection of the online trajectory (or stroke recovery) of offline handwritings has many applications including the forensic application where it can help investigators converting an offline signature into its online equivalent in order to perform the verification. It can also be used in a similar way in handwriting recognition as online handwriting recognition reaches higher recognition rates than offline recognition.
There are several studies regarding the detection of trajectories of handwritings. A survey of such methods is given in [1].

The aim of this competition is to attract the interest of the document analysis community to this research area and to measure the performance of recent advances in this field.

This competition is organized in the scope of the Twelfth International Conference on Document Analysis and Recognition ICDAR2013 that will be held in Washington, DC.

The data collection has been done by all of Wael Al-Ayoubi, Amna Nasser Almejali, Amal Saleh Al-Yazeedi and Roudha Khalid Al-Atiya within a research project NPRP 09 – 864 – 1 – 128 founded by Qatar Foundation and lead by Dr. Somaya Al-Maadeed.


The competition is now live at Kaggle.

Data and Evaluation Procedure

The dataset that will be used in this study is a subset of an Arabic Signature Dataset presented in [2]. This dataset has three occurrences of signatures of about 200 persons.
The systems will be evaluated by matching the ground truth trajectory against the detected trajectory using a dynamic time wrapping scheme as proposed in [3].

Important dates

Soon: competition open.
April 20th: deadline for submissions.
April 30th: competition paper available.


  • Dr. Abdelâali Hassaïne received the “Ingénieur d’Etat” degree in computer science from “Université de Tlemcen”, Algeria in 2005, the “Master recherche” degree in imaging and computer graphics from “INSA de Lyon”, France, in 2006, and the Ph.D. degree in mathematical morphology from “Mines ParisTech”, France, in 2009. From January to July 2010, he worked as a postdoctoral fellowship on the identification and authentication of paintings and artworks in “Université de Saint-Etienne”, France. In January 2011, he joined Qatar University as a postdoctoral fellowship on document management and writer identification. His research interests are in mathematical morphology, feature extraction and document image processing.
  • Dr. Somaya Al-Ma’adeed received her BSc in Computer Science from Qatar University- Qatar in 1994, she received her MSc in Mathematics and Computer Science from Alexandria University-Egypt in 1999, and her PhD in Computer Science from Nottingham University in 2004. Following her BSc, she worked in academia (Qatar University), where she did research in the areas of character recognition, writer identification, speech recognition, tendering systems and document management. She has published around 20 papers in the above general areas. Dr. Somaya is now working as an assistant professor in Computer Science and Engineering department at Qatar University.
  • Prof. Ahmed Bouridane received the “Ingenieur d’Etat” degree in electronics from “Ecole Nationale Polytechnique” of Algiers (ENPA), Algeria, in 1982, the M.Phil. degree in electrical engineering (VLSI design for signal processing) from the University of Newcastle-Upon-Tyne, U.K., in 1988, and the Ph.D. degree in electrical engineering (computer vision) from the University of Nottingham, U.K., in 1992. From 1992 to 1994, he worked as a Research Developer in telesurveillance and access control applications. In 1994, he joined Queen’s University Belfast, Belfast, U.K., initially as Lecturer in computer architecture and image processing and later on he was promoted to Reader in Computer Science. He is now a full Professor in Image Engineering and Security at Northumbria University at Newcastle (UK), and his research interests are in imaging for forensics and security, biometrics, homeland security, image/video watermarking and cryptography. He has authored and co-authored more than 200 publications and one research book. Prof. Bouridane is a Senior Member of IEEE.


[1] Nguyen, Vu, and Michael Blumenstein. Techniques for static handwriting trajectory recovery: a survey. Proceedings of the 9th IAPR International Workshop on Document Analysis Systems. ACM, 2010.

[2] S Al-Maadeed, W Ayouby, A Hassaine, A Al-Mejali, A Al-Yazeedi. Arabic Signature Verification Datasets. In: The International Arab Conference on Information Technology 2012.

[3] Niels, Ralph, and Louis Vuurpijl. Automatic trajectory extraction and validation of scanned handwritten characters. Tenth International Workshop on Frontiers in Handwriting Recognition. 2006.

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