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Face Detection and Recognition Using Combined DRLBP and Sift Features with Fuzzy Classifier

  • Seema AtoleEmail author
  • J. A. Kendule
Conference paper

Abstract

In this research, we have proposed face recognition using combined DRLBP and SIFT features using fuzzy classifier. In recent years, security systems became one among the most exacting systems to secure our assets and defend our privacy. A lot of reliable security system should be developed to avoid losses because of identity theft or fraud. Thus, lots of research has been done to enhance an established security system, particularly systems that area unit supported human identification.” Face recognition system is widely employed in human identification method due to its capability to live and later on establish human identification particularly for security functions. The aim of this project is to develop a non-real-life application of a security lock system employing a face recognition methodology. Dominant rotated local binary pattern (DRLBP) is chosen for the face recognition algorithmic program thanks to its quick response of recognition method and less sensitiveness to noise and interference. First, the image of the individual is captured then the captured image is then transferred to the information developed in MATLAB. During this stage, the captured image compares to the training image within the database to see the individual standing. If the system acknowledges the individual as an authentication person or un-authentication person.

Keywords

Facial recognition Facial identification SIFT features DRLBP Fuzzy classifier 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.SVERI’s College of EngineeringPandharpurIndia

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