Proceedings of the First International Conference on Computing, Communication and Control System, I3CAC 2021, 7-8 June 2021, Bharath University, Chennai, India

Research Article

Palmprint Biometric System using Line based Feature Extraction Methods

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  • @INPROCEEDINGS{10.4108/eai.7-6-2021.2308682,
        author={Sathish  R and Baskar  D and Vinod  Kumar D},
        title={Palmprint Biometric System using Line based Feature Extraction Methods },
        proceedings={Proceedings of the First International Conference on Computing, Communication and Control System, I3CAC 2021, 7-8 June 2021, Bharath University, Chennai, India},
        publisher={EAI},
        proceedings_a={I3CAC},
        year={2021},
        month={6},
        keywords={biometrics palmprint authentication line features object recognition},
        doi={10.4108/eai.7-6-2021.2308682}
    }
    
  • Sathish R
    Baskar D
    Vinod Kumar D
    Year: 2021
    Palmprint Biometric System using Line based Feature Extraction Methods
    I3CAC
    EAI
    DOI: 10.4108/eai.7-6-2021.2308682
Sathish R1,*, Baskar D2, Vinod Kumar D2
  • 1: Research Scholar - Electronics & Communication Engineering, 3Professor & Head - Biomedical Engineering, Vinayaka Mission's Kirupananda Variyar Engineering College, Vinayaka Mission’s Research Foundation (Deemed to be University), Salem, Tamil Nadu, India.
  • 2: Assistant Professor - Electrical & Electronics Engineering, Annai Teresa College of Engineering, Viluppuram, Tamil Nadu, India.
*Contact email: sathishlec25@gmail.com

Abstract

Biometrics is the study of estimating human qualities to confirm or recognize the personality of a person. Palmprint is one of the human physiological attributes acquiring consideration among analysts as the mean of security. The Chinese Academy of Sciences Institute of Automation (CASIA) database is used for investigations. Lines or boundaries carry vital information for object recognition. Principal lines, Wrinkles and Ridges are categorized as line features. Competent Line-based feature extraction methods used for various object recognition are selected and discussed. The palmprint line features are extracted using Prewitt Edge Detector, Sobel operator, Canny Edge Detector, Kirsch Operator and Multiscale Edge Detector. In which Kirsch Operator performs good and achieves 94.95% accuracy for 1% of FAR and 94.85% accuracy for 2% of FAR.