Dissimilarity-based nearest neighbor classifier for single-sample face recognition

2020 ◽  
Author(s):  
Zhengqi Zhang ◽  
Li Zhang ◽  
Meng Zhang
Keyword(s):  
Face Recognition ◽  
Nearest Neighbor ◽  
Single Sample ◽  
Nearest Neighbor Classifier ◽  
Neighbor Classifier

scholarly journals Pengenalan Wajah Menggunakan Metode Linear Discriminant Analysis dan k Nearest Neighbor

2017 ◽  
Vol 9 (1) ◽  
pp. 1-9
Author(s):  
Fandiansyah Fandiansyah ◽  
Jayanti Yusmah Sari ◽  
Ika Putri Ningrum
Keyword(s):  
Feature Extraction ◽  
Face Recognition ◽  
Discriminant Analysis ◽  
Linear Discriminant Analysis ◽  
Nearest Neighbor ◽  
Experimental Result ◽  
K Nearest Neighbor ◽  
Linear Discriminant ◽  
Nearest Neighbor Classifier ◽  
Neighbor Classifier

Face recognition is one of the biometric system that mostly used for individual recognition in the absent machine or access control. This is because the face is the most visible part of human anatomy and serves as the first distinguishing factor of a human being. Feature extraction and classification are the key to face recognition, as they are to any pattern classification task. In this paper, we describe a face recognition method based on Linear Discriminant Analysis (LDA) and k-Nearest Neighbor classifier. LDA used for feature extraction, which directly extracts the proper features from image matrices with the objective of maximizing between-class variations and minimizing within-class variations. The features of a testing image will be compared to the features of database image using K-Nearest Neighbor classifier. The experiments in this paper are performed by using using 66 face images of 22 different people. The experimental result shows that the recognition accuracy is up to 98.33%. Index Terms—face recognition, k nearest neighbor, linear discriminant analysis.

A Decorrelation-Based Nonnegative Matrix Factorization Algorithm for Face Recognition

2013 ◽  
Vol 651 ◽  
pp. 858-863 ◽  
Author(s):  
Dan Zhou ◽  
Hai Yan Gao ◽  
Yun Jie Zhang
Keyword(s):  
Face Recognition ◽  
Matrix Factorization ◽  
Nonnegative Matrix Factorization ◽  
Nearest Neighbor ◽  
Nonnegative Matrix ◽  
Face Image ◽  
Original Matrix ◽  
Nearest Neighbor Classifier ◽  
Factorization Algorithm ◽  
Neighbor Classifier

Nonnegative Matrix Factorization (NMF) is among the most popular subspace methods, widely used in a variety of image processing problems. However, this approach is very time-consuming in face recognition due to the extreme high dimensionality of the original matrix. To remedy this limitation, this paper presents a Decorrelation-based NMF (DNMF) method. The proposed algorithm first takes into account the dimension reduction of the original matrix by preprocessing of decorrelation in spatial domain, and then uses nearest neighbor classifier on the reduced subspace. The developed algorithm has been applied for the ORL standard face image database. Experimental results demonstrate the validity of this method.

Nearest-neighbor classifier motivated marginal discriminant projections for face recognition

2011 ◽  
Vol 5 (4) ◽  
pp. 419-428 ◽  
Author(s):  
Pu Huang ◽  
Zhenmin Tang ◽  
Caikou Chen ◽  
Xintian Cheng
Keyword(s):  
Face Recognition ◽  
Nearest Neighbor ◽  
Nearest Neighbor Classifier ◽  
Neighbor Classifier

FPGA-Based Implementation of Face Recognition Based on Gabor and DCT

2012 ◽  
Vol 241-244 ◽  
pp. 1741-1744
Author(s):  
Guo Hong Lai ◽  
Luo Min ◽  
Song Liu ◽  
Xiao Fang Wang
Keyword(s):  
Face Recognition ◽  
Discrete Cosine Transform ◽  
Nearest Neighbor ◽  
Experimental Results ◽  
Gabor Transform ◽  
Face Database ◽  
Recognition Method ◽  
Cosine Transform ◽  
Nearest Neighbor Classifier ◽  
Neighbor Classifier

A face recognition method based on discrete cosine transform and Gabor transform is proposed. A FPGA-based platform on DE2-115 board is designed by SOPC. We compared our methods with the method based on PC. In the experiments, the nearest neighbor classifier is used to recognize different faces from the Yale face database. Experimental results show that the proposed

A nearest neighbor classifier based on virtual test samples for face recognition

Optik ◽  
2015 ◽  
Vol 126 (21) ◽  
pp. 2799-2803 ◽  
Author(s):  
Ningbo Zhu ◽  
Ting Xu ◽  
Lei Wei ◽  
Ting Tang
Keyword(s):  
Face Recognition ◽  
Nearest Neighbor ◽  
Nearest Neighbor Classifier ◽  
Virtual Test ◽  
Neighbor Classifier
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