Adaptively weighted sub-directional two-dimensional linear discriminant analysis for face recognition

نویسندگان

  • Lijun Yan
  • Jeng-Shyang Pan
  • Shu-Chuan Chu
  • Muhammad Khurram Khan
چکیده

discriminant analysis (AWS2DLDA) is proposed in this paper. AWS2DLDA can extract the directional features of images in the frequency domain, and it is applied to face recognition. Some experiments are conducted to demonstrate the higher than the other popular algorithms.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Supervised Feature Extraction of Face Images for Improvement of Recognition Accuracy

Dimensionality reduction methods transform or select a low dimensional feature space to efficiently represent the original high dimensional feature space of data. Feature reduction techniques are an important step in many pattern recognition problems in different fields especially in analyzing of high dimensional data. Hyperspectral images are acquired by remote sensors and human face images ar...

متن کامل

Kernel-based Weighted Discriminant Analysis with QR Decomposition and Its Application to Face Recognition

Kernel discriminant analysis (KDA) is a widely used approach in feature extraction problems. However, for high-dimensional multi-class tasks, such as faces recognition, traditional KDA algorithms have a limitation that the Fisher criterion is non-optimal with respect to classification rate. Moreover, they suffer from the small sample size problem. This paper presents two variants of KDA called ...

متن کامل

Feature Extraction based on Sub-Pattern Multi-Directional 2DLDA

A novel feature extraction method based on sub-pattern Multi-directional two-dimensional linear discriminate analysis (Sp-MD2DLDA) for face recognition is presented in this paper. In the proposed method, firstly, we apply directional 2DLDA (D2DLDA) to extract features in some initial directions, and then choose the effective directions from the initial directions for feature fusion after an eva...

متن کامل

Face recognition using nonparametric-weighted Fisherfaces

This study presents an appearance-based face recognition scheme called the nonparametric-weighted Fisherfaces (NW-Fisherfaces). Pixels in a facial image are considered as coordinates in a high-dimensional space and are transformed into a face subspace for analysis by using nonparametric-weighted feature extraction (NWFE). According to previous studies of hyperspectral image classification, NWFE...

متن کامل

Combination of Face Direction Estimation and Face Recognition Using Four-Directional Features

To identify people’s faces from various directions, we propose a novel method that distinguishes people using a combination of face direction estimation and face recognition. Both the face direction estimation method and the face recognition method are appearance-based methods that use a linear discriminant analysis on the same features, the Four-Directional Features. Since these methods are co...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • Future Generation Comp. Syst.

دوره 28  شماره 

صفحات  -

تاریخ انتشار 2012