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

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.