Cargando…
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...
Autor principal: | |
---|---|
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 |
_version_ | 1782304139486691328 |
---|---|
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. |
format | Online Article Text |
id | pubmed-3927534 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | Molecular Diversity Preservation International (MDPI) |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT huangkuoyi anautorecognizingsystemfordicegamesusingamodifiedunsupervisedgreyclusteringalgorithm AT huangkuoyi autorecognizingsystemfordicegamesusingamodifiedunsupervisedgreyclusteringalgorithm |