Abstract The work presented in this paper proposes a set of techniques to animate chess moves which are printed on a chess book. Those techniques include (1) extraction of chess moves from an image of printed page, (2) recognition of chess moves from the extracted image, and (3) displaying digitally encoded successive moves as an animation on a chessboard. Since all the moves are temporally related, temporal animations show change of spatial patterns in time. Moreover, it becomes easier to understand how the moves are played out and who leads the game. In this study, we animate chess moves printed in Figurine Algebraic Notation (FAN) notation. The proposed technique also eliminates false recognition by means of controlling possible moves in accordance with the rules of chess semantics.

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[24] Zhu H., Lei J., and Tian, X., A Pattern Recognition System Based on Computer Vision The method of Chinese chess recognition, in Proceedings of the IEEE International Conference on Granular Computing, Hangzhou, pp. 865-868, 2008. 36 The International Arab Journal of Information Technology, Vol. 15, No. 1, January 2018 S leyman Eken has received his BEng. in Computer Engineering from Karadeniz Technical University in 2009 and ME. in Computer Engineering from Kocaeli University in 2012. He is currently working towards Ph.D. degree in Computer Engineering from Kocaeli University, Turkey. Also, he is currently a Research Assistant of Computer Engineering Department at Kocaeli University in Turkey. His current research interests include distributed file systems, data synchronization, Satellite Image Processing, Remote Sensing, WEB-GIS applications and Spatial Databases. Abd lkadir Karaba received the B.S. degree from the Computer Engineering Department, Kocaeli University, Kocaeli, Turkey, in 2015. His research interests include computer vision and pattern recognition. Hayrunnisa Sar received the B.S. degree from the Computer Engineering Department, Kocaeli University, Kocaeli, Turkey, in 2015. Her research interests include computer vision and pattern recognition. Ahmet Sayar received M.S. in Computer Science (2001) from Syracuse University and Ph.D. in Computer Science (2009) from Indiana University, USA. He has worked at Los Alamos National Laboratory (New Mexico, USA) and Community Grids Laboratory (Indiana, USA) as a researcher. Since 2010, he is a professor at Computer Engineering Department, Kocaeli University, Turkey. His current research interests include Distributed Systems, Big Data, Data- Intensive Computing, Remote Sensing, GIS, and Spatial Data-Databases. He has co-authored 3 books and around 70 papers.