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Face Recognition Based on Local Binary Pattern Auto-correlogram

  • Zimei LiEmail author
  • Ping Yu
  • Hui Yan
  • Yixue Jiang
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 157)

Abstract

Face recognition mainly includes face feature extraction and recognition. Color is an important visual feature. Color correlogram (CC) algorithm is commonly used in the color-based image retrieval as a feature descriptor, but most of the existing methods based on CC have problems of high computational complexity and low retrieval accuracy. Aiming at this problem, this paper proposes an image retrieval algorithm based on color auto-correlogram. The new color feature vector which describes the global and spatial distribution relation among different colors is obtained in the CC feature matrix, thus reducing the computational complexity. Inter-feature normalization is applied in color auto-correlogram (CAC) to enhance the retrieval accuracy. The experimental result shows that this integrated method can reduce the computational complexity and improves real-time response speed and retrieval accuracy.

Keywords

Face recognition Local binary pattern Auto-correlogram Support vector machine 

Notes

Acknowledgements

This work is supported by the Science and Technology Department Research Project of Jilin Province (No. 20190302115GX).

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.School of Computer Technology and EngineeringChangchun Institute of TechnologyChangchunChina
  2. 2.Jilin Province S&T Innovation Center for Physical Simulation and Security of Water Resources and Electric Power EngineeringChangchunChina

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