Abstract
Face recognition using FLD for extracting high dimensional images is introduced in this paper. The main purpose is to work on removing bugs and noise from the images and extract the facial expression applied on face descriptor. FLD is selected for increasing the discrimination information [17]. The main points of this paper give the brief knowledge about the face recognition and face clustering. Its shows how biometric terms help the local and global features for extracting information from database. Finding better solutions to deal with noise in face recognition is a challenging task [18]. We also performed some comparative analysis on various face recognition techniques. The main motive of this paper is to increase the recognition rate of the images and provide good efficiency. This method defines how the features and facial expression are extracted and all noise and bugs are eliminated to make a separate individual cluster of same known faces.
Highlights
A face clustering is done by combining two parameters which are face recognition and face detection
Over the past of 30-40 years the scientist had made the replica of neuron system of our brain which helps in the various face recognition technology, having the same property to identify the face just like our brain does
Face recognition has two parameters (1) verification in which the system determines whether the images relates to the individual and check into the database if it is not there the request is rejected.(2) Identification in which the system check the pre-existing data from the database which identify the face if it is from known individuals or not[1]
Summary
A face clustering is done by combining two parameters which are face recognition and face detection. Face recognition has two parameters (1) verification in which the system determines whether the images relates to the individual and check into the database if it is not there the request is rejected.(2) Identification in which the system check the pre-existing data from the database which identify the face if it is from known individuals or not[1]. Biometric is the approach which is used for face recognition having a different pattern like physical or behaviour characteristic. One of biometric approach is physical characteristics in which the recognition of the user is identified by his body parts just like eyes, nose, chin, voice, fingerprints, iris, photos and DNA etc. After the identification of faces it matches from the existing database which is known as face detection and according to recognition and detection of faces, the system put similar known individuals in one group and another individuals in another group that's how the cluster is made
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