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.
Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort or service provider interaction. In cloud computing, load balancing is one of the key issues. Load balancing is the process of apportioning the load among various nodes of a distributed...
In this paper, we propose to segment the human face using marker based watershed segmentation, an improved version of watershed segmentation. This algorithm uses the concept of markers as a pre requisite to determine the segments. The proposed method extracts facial features, most importantly the eyes and the lips. The successful feature extraction of the human face can contribute in a significant...
Face Recognition is the process of identification of a person by his facial image. As applied to face recognition, this paper proposes a method, comprising of Laplacian of Gaussian (LoG) filter for intricate facial detail enhancement, Singular Value Decomposition (SVD) for holistic feature extraction and Feed forward Neural Network (FFNN) for classification. Applications of LoG filter highlights,...
Face Recognition Technology is one of the fastest growing field in the biometric industries. Although human seem to recognize faces with relative ease, machine recognition of faces is a challenging task. In this direction the paper proposed here is an automatic face recognition technique based on curvelets and Singular Value decomposition (SVD). Curve discontinuities present in the face images are...
One of the challenges the face recognition application is facing today is that of the high dimensionality of multivariate data. In this context, this paper proposes to compare the performance of a triumvirate combination of linear dimensionality reduction techniques namely Singular Value Decomposition (SVD) which maximizes the variance of the training vectors, Direct Fractional Linear Discriminant...
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.