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Type-2 Fuzzy Logic in Pattern Recognition Applications

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Type-2 Fuzzy Logic and Systems

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 362))

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Abstract

Type-2 fuzzy systems can be of great help in image analysis and pattern recognition applications. In particular, edge detection is a process usually applied to image sets before the training phase in recognition systems. This preprocessing step helps to extract the most important shapes in an image, ignoring the homogeneous regions and remarking the real objective to classify or recognize. Many traditional and fuzzy edge detectors can be used, but it is very difficult to demonstrate which one is better before the recognition results are obtained. In this work we show experimental results where several edge detectors were used to preprocess the same image sets. Each resulting image set was used as training data for a neural network recognition system, and the recognition rates were compared. In this paper we present the advantage of using a general type-2 fuzzy edge detector method in the preprocessing phase of a face recognition system. The Sobel and Prewitt edge detectors combined with GT2 FSs are considered in this work. In our approach, the main idea is to apply a general type-2 fuzzy edge detector on two image databases to reduce the size of the dataset to be processed in a face recognition system. The recognition rate is compared using different edge detectors including the fuzzy edge detectors (type-1, interval, and general type-2 FS) and the traditional Prewitt and Sobel operators.

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Authors and Affiliations

  1. Tijuana Institute of Technology, Tijuana, Mexico

    Patricia Melin

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  1. Patricia Melin
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Correspondence to Patricia Melin .

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Editors and Affiliations

  1. LUCID Research Group, School of Computer Science, The University of Nottingham, Jubilee Campus, Nottingham, Nottinghamshire, United Kingdom

    Robert John

  2. School of Computer Science and Electronic Engineering, The Computational Intelligence Centre, University of Essex, Colchester, United Kingdom

    Hani Hagras

  3. Division of Graduate Studies, Tijuana Institute of Technology, Tijuana, Baja California, Mexico

    Oscar Castillo

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Melin, P. (2018). Type-2 Fuzzy Logic in Pattern Recognition Applications. In: John, R., Hagras, H., Castillo, O. (eds) Type-2 Fuzzy Logic and Systems. Studies in Fuzziness and Soft Computing, vol 362. Springer, Cham. https://doi.org/10.1007/978-3-319-72892-6_5

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  • DOI: https://doi.org/10.1007/978-3-319-72892-6_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-72891-9

  • Online ISBN: 978-3-319-72892-6

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