Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11889/8284
Title: Chessboard recognition system using signature, principal component analysis and color information
Authors: Khater, Ismail M. 
Ghorab, Ahmed S. 
Aljarrah, Inad A. 
Keywords: Euclidean Distance;Chess - Computer games;Computer vision;Permanent Court of Arbitration - Rules and practice
Issue Date: 2012
Publisher: 2012 2nd International Conference on Digital Information Processing and Communications, ICDIPC 2012
Abstract: This paper aims to implement a computer vision technique to translate an image into a description that can be read by computer programs to make decisions. The proposed system is applied to chessboard with a set of objects (pieces), and outputs the pieces names, locations, in addition to the pieces' colors. The signature feature has been used to distinguish the pieces types but when the signature comes to grief, the PCA (Principal Components Analysis) is used, and then the object color is obtained. The proposed system was trained and tested using Matlab, based on a set of collected samples using chessboard images. The simulation results show the effectiveness of the proposed method to recognize the pieces locations, types, and colors.
URI: http://hdl.handle.net/20.500.11889/8284
DOI: 10.1109/ICDIPC.2012.6257285
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