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Multi-Feature Pattern Recognition

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Computational Intelligence in Multi-Feature Visual Pattern Recognition

Part of the book series: Studies in Computational Intelligence ((SCI,volume 556))

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Abstract

This chapter focuses on feature selection and classification of multi-feature patterns. Micro array based cancer classification and image based face recognition are discussed. A detailed review of hand gesture recognition algorithms and techniques is included. The hand gesture recognition algorithms are surveyed by classifying them into three categories (a) hidden Markov model based methods, (b) neural network and learning based methods, and (c) the other methods. A list of available hand gesture databases is provided.

The way is long if one follows precepts, but short... if one follows patterns

Lucius Annaeus Seneca.

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Authors and Affiliations

  1. Inst. of High Performance Computing, A*STAR, Singapore, Singapore

    Pramod Kumar Pisharady

  2. Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore

    Prahlad Vadakkepat & Loh Ai Poh

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  1. Pramod Kumar Pisharady
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  2. Prahlad Vadakkepat
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  3. Loh Ai Poh
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Correspondence to Pramod Kumar Pisharady .

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Pisharady, P.K., Vadakkepat, P., Poh, L.A. (2014). Multi-Feature Pattern Recognition. In: Computational Intelligence in Multi-Feature Visual Pattern Recognition. Studies in Computational Intelligence, vol 556. Springer, Singapore. https://doi.org/10.1007/978-981-287-056-8_3

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  • DOI: https://doi.org/10.1007/978-981-287-056-8_3

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