Biometric Access Using Image Processing Semantics

  • C. AswinEmail author
  • N. Dhilip Raja
  • N. Angel
  • K. Sudha
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 35)


We propose a model-based approach for accessing a magnetic lock in the door using face recognition. We Implement Face Recognition by using image processing semantics. The Facial recognition uses facial landmarks such as chin, eyebrow, nose, eyes and lip to encode the user’s face. The encoded signal is sent to the lock via WIFI. We interfaced the facial recognition module through an android app and implemented the backend using python server. Our approach here is by using KNN algorithm which is one among the various machine learning algorithm. The K-nearest neighbor algorithm is used to classify the facial landmarks which is calculated by Euclidian distance formula which calculates the distance between the markers. The Face recognition module runs through python which is used for connectivity between the magnetic lock and backend. The magnetic lock is implemented using Node MC, switch, electromagnet and a power supply.


Facial landmarks WIFI Android app Python server 


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Computer Science EngineeringSt. Joseph’s College of EngineeringChennaiIndia

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