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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| Format: | Article |
| Language: | English |
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MDPI AG
2008-02-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/8/2/1212/ |
| _version_ | 1798024425373696000 |
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| author | Kuo-Yi Huang |
| author_facet | Kuo-Yi Huang |
| author_sort | Kuo-Yi Huang |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-04-11T18:02:21Z |
| format | Article |
| id | doaj.art-b42328074ffe4624996eca3851f2ccac |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T18:02:21Z |
| publishDate | 2008-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-b42328074ffe4624996eca3851f2ccac2022-12-22T04:10:26ZengMDPI AGSensors1424-82202008-02-018212121221An Auto-Recognizing System for Dice Games Using a Modified Unsupervised Grey Clustering AlgorithmKuo-Yi HuangIn 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.http://www.mdpi.com/1424-8220/8/2/1212/Machine visionGrey relational analysisGrey clusteringDiceAuto- recognition. |
| spellingShingle | Kuo-Yi Huang An Auto-Recognizing System for Dice Games Using a Modified Unsupervised Grey Clustering Algorithm Sensors Machine vision Grey relational analysis Grey clustering Dice Auto- recognition. |
| 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 | Machine vision Grey relational analysis Grey clustering Dice Auto- recognition. |
| url | http://www.mdpi.com/1424-8220/8/2/1212/ |
| work_keys_str_mv | AT kuoyihuang anautorecognizingsystemfordicegamesusingamodifiedunsupervisedgreyclusteringalgorithm AT kuoyihuang autorecognizingsystemfordicegamesusingamodifiedunsupervisedgreyclusteringalgorithm |