计算机应用 ›› 2005, Vol. 25 ›› Issue (04): 760-762.DOI: 10.3724/SP.J.1087.2005.0760

• 图形图像处理 • 上一篇    下一篇

一种基于二维隐马尔可夫模型的图像分类算法

胡迎松1,朱阿柯1,陈刚2,陈中新3   

  1. 1.华中科技大学计算机科学与技术学院; 2.武汉科技大学计算机科学与技术学院; 3.湖北清江水电开发有限责任公司
  • 发布日期:2005-04-01 出版日期:2005-04-01

Algorithm of image classification based on two-dimensional hidden Markov model

HU Ying-song1,ZHU A-ke1,CHEN Gang2,CHEN Zhong-xin3   

  1. 1.College of Computer Science and Technology,Huazhong University of Science and Technology,Wuhan Hubei 430074,China; 2.College of Computer Science and Technology,Wuhan University of Science and Technology,Wuhan Hubei 430081,China; 3.The Limited Company of Water and Electricity Development of Qing River,Yichang Hubei 443002,China
  • Online:2005-04-01 Published:2005-04-01

摘要:

针对图像分块之间的相互依赖关系,提出一种基于二维隐马尔可夫模型的图像分类算 法。该算法将一维隐马尔可夫模型扩展成二维隐马尔可夫模型,模型中相邻的图像分块在平面两个 方向上按条件转移概率进行状态转换,反应出两个维上的依赖关系。隐马尔可夫模型参数通过期望 最大化算法(EM)来估计。同时,本文利用二维Viterbi算法,在训练隐马尔可夫模型的基础上,实现 对图像进行最优分类。文件图像分割的应用表明,隐马尔可夫算法优于CART算法。

关键词: 二维隐马尔可夫模型, 图像分类, EM算法, Viterbi算法

Abstract:

Aimed at the inter-block dependency, an image classification algorithm based on a two hidden Markov model(2DHMM) extension from the one dimensional HMM was developed. The 2DHMM has transition probabilities conditioned on the states of neighboring blocks from both directions. Thus, the dependency in two dimensions can be reflected simultaneously. The HMM parameters were estimated by the EM algorithm. A two dimensional version of the Viterbi algorithm was also developed to classify optimally an image based on the trained HMM. Application of the HMM algorithm to document image shows that the algorithm performs better than CART.

Key words: two-dimensional hidden Markov model, image classification, EM algorithm, viterbi algorithm

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