计算机与现代化 ›› 2014, Vol. 0 ›› Issue (1): 32-36.

• 图像处理 • 上一篇    下一篇

基于神经网络的字牌识别系统

  

  1. 华南理工大学软件学院,广东广州510006
  • 收稿日期:2013-09-09 出版日期:2014-01-20 发布日期:2014-02-10
  • 作者简介:周旭峰(1984-),男,湖南娄底人,华南理工大学软件学院硕士研究生,研究方向:先进计算机体系结构。

Automatically Deal Chinese Suit Tiles Machine Based on Neural Networks Technology

  1. School of Software, South China University of Technology, Guangzhou 510006, China
  • Received:2013-09-09 Online:2014-01-20 Published:2014-02-10

摘要: 设计基于BP神经网络的字牌识别系统,可用于实现字牌自动发牌机,以克服字牌比赛中人工洗牌的弊端。为提高系统的识别正确率,对字牌图像进行特定处理:(1)对图像像素数据通过闭运算、膨胀运算和腐蚀运算衍生出多种标准特征矩阵以增加训练样本,(2)挖掘图像特征数据规律提取颜色特征值和大小写特征值,组成特征向量并依此对图像进行分类编组,用特定编组的特征矩阵训练对应编组的BP神经网络。仿真结果表明,该系统识别正确率高,适应字牌比赛对自动发牌机的要求。

关键词:  , BP神经网络, 图像处理, 分类, 识别, 字牌自动发牌机

Abstract: The Chinese suit tiles recognition system based on BPNN technology is designed to realize the automatically deal Chinese suit tiles machine to overcome a sort of drawbacks brought by artificial shuffle. In order to improve the accuracy of the recognition system, the training images are preprocessed: on the one hand, many kinds of standard features matrix are derived by the closing operation, dilation operation and erosion operation to increase the number of training samples, on the other hand, some regularities are found out and the color eigenvalues and the case eigenvalues are extracted, then the images and the BPNN are classified by these eigenvalues. The simulation results shows this technique is of high rate of classified accuracy and can meet the needs in the competition practical application of Chinese suit tiles.

Key words: BP neural network, image processing, classification, recognition, automatically deal Chinese suit tiles machine