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Recognition of Skin Diseases Using Curvelet Transforms and Law’s Texture Energy Measures

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Soft Computing Applications (SOFA 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1222))

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Abstract

This work presents an automated system to recognize human skin disease. In many computer vision and pattern recognition problems, such as our case, considering only a single descriptor to mine one sort of feature vector is not enough to attain the entire relevant information from the input data. Therefore, it is required to apply more than one descriptor to extract more than one feature vector categories with different dimensions. In this paper, for the purpose of skin disease classification, we propose a new hybrid method which is the combination of two methods to proficiently classify different types of feature vectors in their original form, dimensionality. The first one uses the Curvelet transform method in spatial and frequency viewpoint and the second one uses the set of energy measures to define textures had been formulated by Law’s texture energy measure. Minimum euclidean distance of the Law’s texure energy measures between different species are calculated for discrimination.

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Author information

Authors and Affiliations

  1. School of Education Technology, Jadavpur University, Kolkata, India

    Jyotismita Chaki

  2. Department of Information Technology, Techno India College of Technology, Kolkata, India

    Nilanjan Dey

  3. Department of Electronics and Instrumentation Engineering, St. Joseph’s College of Engineering, Chennai, 600 119, Tamilnadu, India

    V. Rajinikanth

  4. Department of Electronics and Electrical Communications Engineering, Faculty of Engineering, Tanta University, Tanta, Egypt

    Amira S. Ashour

  5. College of Information and Engineering, Wenzhou Medical University, Wenzhou, China

    Fuqian Shi

Authors
  1. Jyotismita Chaki
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  2. Nilanjan Dey
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  3. V. Rajinikanth
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  4. Amira S. Ashour
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  5. Fuqian Shi
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Corresponding author

Correspondence to V. Rajinikanth .

Editor information

Editors and Affiliations

  1. "Aurel Vlaicu" University of Arad, Faculty of Engineering, Arad, Romania

    Valentina Emilia Balas

  2. Faculty of Engineering and Information Technology, University of Technology Sydney, Centre for Artificial Intelligence, Sydney, Australia

    Lakhmi C. Jain

  3. Faculty of Engineering, “Aurel Vlaicu” University of Arad, Arad, Arad, Romania

    Marius Mircea Balas

  4. Department of Information Technology and Programming, Azerbaijan Technical University, Baku, Azerbaijan

    Shahnaz N. Shahbazova

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Chaki, J., Dey, N., Rajinikanth, V., Ashour, A.S., Shi, F. (2021). Recognition of Skin Diseases Using Curvelet Transforms and Law’s Texture Energy Measures. In: Balas, V., Jain, L., Balas, M., Shahbazova, S. (eds) Soft Computing Applications. SOFA 2018. Advances in Intelligent Systems and Computing, vol 1222. Springer, Cham. https://doi.org/10.1007/978-3-030-52190-5_4

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