Abstract
So far many methods of recognizing the face arose, each has the merits and demerits. Among these methods are methods based on Hidden Markov models, and their advantage is the high efficiency. However, the traditional HMM uses one-dimensional data, which is not a good solution for image processing, because the images are two-dimensional. Transforming the image in a one-dimensional feature vector, we remove some of the information that can be used for identification. The article presents the full ergodic 2D-HMM and applied for face identification.
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Bobulski, J. (2016). 2DHMM-Based Face Recognition Method. In: Choraś, R. (eds) Image Processing and Communications Challenges 7. Advances in Intelligent Systems and Computing, vol 389. Springer, Cham. https://doi.org/10.1007/978-3-319-23814-2_2
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DOI: https://doi.org/10.1007/978-3-319-23814-2_2
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