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

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...

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Detalles Bibliográficos
Autor principal: Huang, Kuo-Yi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3927534/
https://www.ncbi.nlm.nih.gov/pubmed/27879761
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author Huang, Kuo-Yi
author_facet Huang, Kuo-Yi
author_sort Huang, Kuo-Yi
collection PubMed
description 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.
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spelling pubmed-39275342014-02-18 An Auto-Recognizing System for Dice Games Using a Modified Unsupervised Grey Clustering Algorithm Huang, Kuo-Yi Sensors (Basel) Full Research Paper 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. Molecular Diversity Preservation International (MDPI) 2008-02-21 /pmc/articles/PMC3927534/ /pubmed/27879761 Text en © 2008 by MDPI Reproduction is permitted for noncommercial purposes.
spellingShingle Full Research Paper
Huang, Kuo-Yi
An Auto-Recognizing System for Dice Games Using a Modified Unsupervised Grey Clustering Algorithm
title An Auto-Recognizing System for Dice Games Using a Modified Unsupervised Grey Clustering Algorithm
title_full An Auto-Recognizing System for Dice Games Using a Modified Unsupervised Grey Clustering Algorithm
title_fullStr An Auto-Recognizing System for Dice Games Using a Modified Unsupervised Grey Clustering Algorithm
title_full_unstemmed An Auto-Recognizing System for Dice Games Using a Modified Unsupervised Grey Clustering Algorithm
title_short An Auto-Recognizing System for Dice Games Using a Modified Unsupervised Grey Clustering Algorithm
title_sort auto-recognizing system for dice games using a modified unsupervised grey clustering algorithm
topic Full Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3927534/
https://www.ncbi.nlm.nih.gov/pubmed/27879761
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