Abstract
Facial recognition technology is the process for identifying or verifying a face from digital images. The need for face recognition has been of real importance with the development of modern society. Detection and recognition of faces has been on the rise worldwide owing the requirement for security for economic transactions, authorization, national safety and security and other important factors. The technology comprises of face detection, database creation and face recognition. This paper presents a new approach of face identification using LBP method and Haar-like features. The first step is face detection which is done using Haar cascade classifier. After detection, a face is saved in the database. Then the faces from the database are passed through the face recognition algorithm. The Local Binary Pattern Histogram (LBPH) method is used for face recognition. The performance of face detection can be seen to produce maximum error of 1.6%, 2.1% and 0.8% in case of Real-Time video, image file and video file respectively which may be considered accurate. The recognition algorithm produces maximum error of 0.4% which may be considered accurate as well.
Highlights
INTRODUCTIONFacial recognition technologies have grown fast in the last few years. Effective facial detection and identification is important today in the fields of social development, public safety, national security and others [1]
In a video stream or an image, face detection is implemented for finding a human face and its poses
This paper proposes a method of face detection using Haar cascade classifier [4]
Summary
Facial recognition technologies have grown fast in the last few years. Effective facial detection and identification is important today in the fields of social development, public safety, national security and others [1]. In a video stream or an image, face detection is implemented for finding a human face and its poses It is one of the most important information processing approaches. In case of skin color based detection, background of the image can cause interference with the normal processing and recognition of the faces. After the use of Haar-like feature for face detection, the local feature recognition, LBP (Local Binary Patterns) [5] method is utilized for face recognition. The process first detects the face region from 2D images and the corresponding depth map is captured with a Kinect Camera which is extracted with cascade object detector. The procedure followed in this paper uses global features for recognition and local features for authentication.
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