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Local directional gradient pattern: a local descriptor for face recognition

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A Correction to this article was published on 18 January 2018

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Abstract

In this paper a local pattern descriptor in high order derivative space is proposed for face recognition. The proposed local directional gradient pattern (LDGP) is a 1D local micropattern computed by encoding the relationships between higher order derivatives of the reference pixel in four distinct directions. The proposed descriptor identifies relationship between the high order derivatives of the referenced pixel in four different directions to compute the micropattern which corresponds to the local feature. Proposed descriptor considerably reduces the length of the micropattern which consequently reduces the extraction time and matching time while maintaining the recognition rate. Results of the extensive experiments conducted on benchmark databases AT&T, Extended Yale B and CMU-PIE show that the proposed descriptor significantly reduces the extraction as well as matching time while the recognition rate of the descriptor is almost similar to existing state of the art methods. Moreover the proposed descriptor is more resistant against the AWGN compared to the other state of the art descriptors used for face recognition problems.

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Change history

  • 18 January 2018

    The Eqs. 3 and 15 in the original version of this article contained an error.

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Authors and Affiliations

  1. Department of Information Technology, Indian Institute of Information Technology, Allahabad, India

    Soumendu Chakraborty, Satish Kumar Singh & Pavan Chakraborty

Authors
  1. Soumendu Chakraborty
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  2. Satish Kumar Singh
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  3. Pavan Chakraborty
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Corresponding author

Correspondence to Soumendu Chakraborty.

Additional information

A correction to this article is available online at https://doi.org/10.1007/s11042-018-5612-6.

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Chakraborty, S., Singh, S.K. & Chakraborty, P. Local directional gradient pattern: a local descriptor for face recognition. Multimed Tools Appl 76, 1201–1216 (2017). https://doi.org/10.1007/s11042-015-3111-6

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  • DOI: https://doi.org/10.1007/s11042-015-3111-6

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