Multiple Face Detection Using Hybrid Features with SVM Classifier

  • Sandeep KumarEmail author
  • Sukhwinder Singh
  • Jagdish Kumar
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 847)


Nowadays, multiple face detection (MFD) and extraction play an important role in face identification for various applications. In the proposed algorithm, Support Vector Machine (SVM) has been used for multiple face detection, and Discrete Wavelet Transform (DWT), Edge Histogram (EH), and Auto-correlogram (AC) are used for feature extraction. The proposed methodology worked on two different database i.e. Carnegie Mellon University (CMU) and BAO database for MFD. In this research paper, the proposed methodology gives a better result than the existing technique. Finally, our accuracy raised up to 90% approximately.


Face detection SVM DWT Edge Histogram Correlogram Median filter 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Sandeep Kumar
    • 1
    Email author
  • Sukhwinder Singh
    • 1
  • Jagdish Kumar
    • 2
  1. 1.Department of Electronics & CommunicationPEC University of TechnologyChandigarhIndia
  2. 2.Department of Electrical EngineeringPEC University of TechnologyChandigarhIndia

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