Manuscript received on August 07, 2020. | Revised Manuscript received on August 15, 2020. | Manuscript published on August 30, 2020. | PP: 354-358 | Volume-9 Issue-6, August 2020. | Retrieval Number: F1483089620/2020©BEIESP | DOI: 10.35940/ijeat.F1483.089620
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
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 . 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 . 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.
Keywords: Face Recognition, Biometric, Local and Global features, FLD, Face Clustering, Gabor Wavelet