The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
The collaborative representation classification (CRC) exhibits superiority in both accuracy and computational efficiency. However, when representing the test sample by a linear combination of the training samples, the CRC does not account for the following: the probability of the test sample being from the same class as the training sample far from it is small. In this paper, we propose the algorithm,...
It is a great challenge for face recognition with single training sample per person. In this paper, we try to propose a new algorithm based sparse representation to solve this problem. The algorithm takes the two-dimensional training samples as the training set directly rather than image vectors. So we can obtain the dictionary of sparse representation only using one sample. The proposed algorithm...
Principal component analysis (PCA) has been widely used in face recognition. Previous literatures show that block PCA can outperform PCA in classification accuracy of face images. We note that block PCA is always based on a non-overlapping partition scheme. In this paper, we propose a novel block PCA method, i.e. overlapping block PCA. This method first partitions every image into a number of blocks...
Two-Dimension Linear Discriminant Analysis (2DLDA) and complex-matrix LDA are two noticeable improvements to conventional LDA. They can achieve a good performance respectively. However, the complex-matrix LDA is very suitable for bimodal biometrics. In this paper, we indicate the two available implementation procedures of complex-matrix, i.e. the original implementation procedure and one alternative...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.