title: An Auto-Recognizing System for Dice Games Using a Modified Unsupervised Grey Clustering Algorithm.
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.
authors.affiliation: Department of Mechatronic Engineering, Huafan University, Taipei, Taiwan. kyhuang@cc.hfu.edu.tw.
authors.forename: Kuo-Yi
authors.initials: KY
authors.lastname: Huang
keywords: Auto- recognition.; Dice; Grey clustering; Grey relational analysis; Machine vision