Next Article in Journal
Next Article in Special Issue
Previous Article in Journal
Previous Article in Special Issue
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

Received: 17 November 2007; Accepted: 14 February 2007 / Published: 21 February 2008
(This article belongs to the Special Issue Intelligent Sensors)
View Full-Text   |   Download PDF [437 KB, uploaded 21 June 2014]
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.

Export to BibTeX |
EndNote


MDPI and ACS Style

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

AMA Style

Huang K-Y. An Auto-Recognizing System for Dice Games Using a Modified Unsupervised Grey Clustering Algorithm. Sensors. 2008; 8(2):1212-1221.

Chicago/Turabian Style

Huang, Kuo-Yi. 2008. "An Auto-Recognizing System for Dice Games Using a Modified Unsupervised Grey Clustering Algorithm." Sensors 8, no. 2: 1212-1221.


Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert