Description

Multiface recognition using OpenCV

Abstract

          Face recognition can be considered one of the most successful biometric identification methods among several types of biometric identification including fingerprints, DNA, palm print, hand geometry, iris recognition, retina and odour/scent. Face recognition provides biometric identification that utilizes the uniqueness of faces for security purposes. The problem with face recognition using biometric identification is its lengthy process and the accuracy of the results. This paper proposes solutions for a faster face recognition process with accurate results. The proposed face recognition process was done using a hybrid process of Haar Cascades and Eigenface methods, which can detect multiple faces (55 faces) in a single detection process. This improved face recognition approach was able to recognize multiple faces with 91.67% accuracy level.

Proposed system

      In the implementation of the proposed face recognition process,it begins with capturing images using a webcam to get training data, which then goes through the face detection process, feature extraction process, and then the core of the face recognition to get the results. The results are sent to the database.

Applications

• Unlock Phones and Laptops and other devices-Authentication
• Identify Crime person
• Help blind people
• Smarter Advertising
• Diagnose disease
• Track Attendance