Comparison of the Effectiveness of 1D and 2D Hmm in the Pattern Recognition

J. Bobulski
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引用次数: 4

Abstract

Abstract Hidden Markov Model (HMM) is a well established technique for image recognition and has also been successfully applied in other domains such as speech recognition, signature verification and gesture recognition. HMM is widely used mechanism for pattern recognition based on 1D data. For images one dimension is not satisfactory, because the conversion of one-dimensional data into a twodimensional lose some information. This paper presents a solution to the problem of 2D data by developing the 2D HMM structure and the necessary algorithms.
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一维和二维Hmm在模式识别中的有效性比较
隐马尔可夫模型(HMM)是一种成熟的图像识别技术,在语音识别、签名验证和手势识别等领域也得到了成功的应用。HMM是一种基于一维数据的模式识别机制。对于图像来说,一维是不能令人满意的,因为将一维数据转换为二维会损失一些信息。本文通过发展二维HMM结构和必要的算法,提出了一种解决二维数据问题的方法。
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