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Techno-Societal 2018 pp 13–23Cite as

3D-DWT and CNN Based Face Recognition with Feature Extraction Using Depth Information and Contour Map

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Abstract

This paper presents a method for face recognition with a combination of skin colour information and depth approach with high security and accuracy for authentication of users. It presents an algorithm for the detection and recognition of the face. For getting higher accuracy in face detection various methods are used, such as template matching method, haar cascade feature, AdaBoost algorithm. To identify real or fake (picture) face depth value determined from the depth map is used. 3D-DWT is used to extract features from the depthmap. Extracted features are used to train the convoluted neural network (CNN).

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Author information

Authors and Affiliations

  1. Walchand College of Engineering, Sangli, India

    Chanchal Mahadev Patil & Sachin D. Ruikar

Authors
  1. Chanchal Mahadev Patil
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  2. Sachin D. Ruikar
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Corresponding author

Correspondence to Sachin D. Ruikar .

Editor information

Editors and Affiliations

  1. SVERI’s College of Engineering, Pandharpur, Maharashtra, India

    Prashant M. Pawar

  2. SVERI’s College of Engineering, Pandharpur, Maharashtra, India

    Babruvahan P. Ronge

  3. Bhabha Atomic Research Centre, Mumbai, Maharashtra, India

    R. Balasubramaniam

  4. SVERI’s College of Engineering, Pandharpur, Maharashtra, India

    Anup S. Vibhute

  5. SVERI’s College of Engineering, Pandharpur, Maharashtra, India

    Sulabha S. Apte

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Patil, C.M., Ruikar, S.D. (2020). 3D-DWT and CNN Based Face Recognition with Feature Extraction Using Depth Information and Contour Map. In: Pawar, P., Ronge, B., Balasubramaniam, R., Vibhute, A., Apte, S. (eds) Techno-Societal 2018 . Springer, Cham. https://doi.org/10.1007/978-3-030-16848-3_2

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