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Sensors 2008, 8(2), 1212-1221; doi:10.3390/s8021212
Article

An Auto-Recognizing System for Dice Games Using a Modified Unsupervised Grey Clustering Algorithm

Department of Mechatronic Engineering, Huafan University, Taipei, Taiwan
Received: 17 November 2007 / Accepted: 14 February 2007 / Published: 21 February 2008
(This article belongs to the Special Issue Intelligent Sensors)
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Abstract

In this paper, a novel identification method based on a machine vision system is proposed to recognize the score of dice. The system employs image processing techniques, and the modified unsupervised grey clustering algorithm (MUGCA) to estimate the location of each die and identify the spot number accurately and effectively. The proposed algorithms are substituted for manual recognition. From the experimental results, it is found that this system is excellent due to its good capabilities which include flexibility, high speed, and high accuracy.
Keywords: Machine vision; Grey relational analysis; Grey clustering; Dice; Auto- recognition. Machine vision; Grey relational analysis; Grey clustering; Dice; Auto- recognition.
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Huang, K.-Y. An Auto-Recognizing System for Dice Games Using a Modified Unsupervised Grey Clustering Algorithm. Sensors 2008, 8, 1212-1221.

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