Study on the chessboard recognition and positioning method of chess game system

DOI

10.2991/isrme-15.2015.63How to use a DOI?

Keywords

augmented reality; SIFT feature matching; k-means clustering; chessboard recognition; checkerboard positioning

Abstract

With the wide application of augmented reality technology, designing a remote chess game based on augmented reality technology has the research significance of potential. The system can make two people both living in different places to play chess as they are playing face to face and can communicate with each other. This paper presents a new methods for identifying the chess board areas in the scene which based on SIFT feature matching and K-means clustering. This paper presents a method of automatically obtaining segmentation threshold based on the parameters of the linear distance difference which can used to exclude the extra line detected and ultimately determine the linear model of 9*10. The experiment proved that the method proposed in this paper can effectively remove the restricted conditions that the camera can only shoot board area and the camera must be taken perpendicular to the board and the method can coordinate position of accurate positioning checkerboard. This method can be reference for similar problems.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Huibai Wang
AU  - Xiao Liu
AU  - Ming Shi
PY  - 2015/04
DA  - 2015/04
TI  - Study on the chessboard recognition and positioning method of chess game system
BT  - Proceedings of the 2015 International Conference on Intelligent Systems Research and Mechatronics Engineering
PB  - Atlantis Press
SP  - 272
EP  - 277
SN  - 1951-6851
UR  - https://doi.org/10.2991/isrme-15.2015.63
DO  - 10.2991/isrme-15.2015.63
ID  - Wang2015/04
ER  -