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.
Measuring similarity between images is required in many multimedia applications such as retrieving perceptually similar images. The most widely used metric for measuring the distance between two signal vectors is mean square error. Even though MSE provides mathematical tractability, it is not suitable for detecting perceptual similarity between images. In this paper, we propose a new measure to calculate...
Educational data mining is being implemented to find important information from huge amount of data collected over a large period of time and to improve the overall quality of students' performance. The authors collected higher education data from several institutions and applied various Data analysis methods such as principal component analysis and two step clustering method to reduce the dimension...
In today's world power consumption is a burning issue. Research is going on to find out various new power efficient design techniques. Power dissipation could be reduced by transforming continuous-time current-steering circuits into discrete-time charge-steering circuits. Charge steering shows all potential to emerge as an effective technique to reduce power dissipation for high-speed circuits. This...
Data Analysis is key to understand the importance of accumulated data over a period of time. The importance of the accumulated data is understood by the data analyst over period of time. The authors had shown the importance of the data collected of the higher education by finding the new and un-identified facts using the statistically techniques. The authors found that the regression techniques could...
Automatic image retrieval similar to a query image is an important task in computer vision. To obtain this goal, every image in database needs to be modeled. A signature is learned for each image and stored. A sparsity based image content modeling and retrieval is proposed in this paper. Sparsity based data modeling has been successfully applied across various areas of image processing. A dictionary...
Texture detection plays an important role in many computer vision tasks. Application ranges from finding an object in satellite images to anomaly detection in medical imaging. Recently sparse representation based texture modeling and detection scheme is proposed. One major drawback using such a generative data modeling is the time taken for texture detection. In this paper we propose and investigate...
Centric Query Processing in Heterogeneous Wireless Sensor Network is the new emerging area of wireless sensor network which provides better interaction with physical world in effective and efficient manner. Previous work provides interaction between homogeneous wireless sensor network. In this paper, we have proposed a centric query processing approach which provides effective communication between...
Rapid changes in internet and network technologies facilitated easy to access online applications, services and database. Database as a service (DaaS) is a model that offer its users to perform data processing (store, modify and retrieve) as long as they are connect to internet. Providing security to database as service model became a challenging work due to malicious network administrator, they exploit...
Texture identification is an important preliminary step in many computer vision applications. There exists supervised and unsupervised approaches to solve this problem. One of the widely used unsupervised technique is KMeans which identifies the region of image based on clustering. The disadvantage of the KMeans technique is that it is an off-line approach that needs all the data prior to processing...
Face detection is an important and challenging task in many computer vision applications. Signal processing using sparse framework has seen much interest in various areas in the recent past. In this paper, we propose a sparse framework based methodology to model a human face using very few training faces. We propose to use SIFT, LBP and RGB based feature vectors to model and detect the face in the...
Feature vector plays an important role in many computer vision applications such as image registration, face recognition, object tracking etc. In many cases, the dimension of the extracted feature vectors using algorithms such as SIFT (Scale-Invariant Feature Transform), SURF (Speeded Up Robust Features), PFH (Point Feature Histogram), FPFH (Fast Point Feature Histogram) etc. can be very large. At...
Region segmentation is an important and challenging task. The applications range from tumour detection in medical imaging, computer aided surveillance, object location, pattern separation etc. Sparsity based data modelling in recent times have produced state of the art results in many image processing tasks. In this paper, we propose a semi-interactive region segmentation in sparse framework. Proper...
In recent times sparse framework based signal modelling has been extensively used in various signal processing tasks. State-of-the-art results have been obtained using this approach in various image processing applications. In this paper, we have adopted the sparse framework for the task of detection of various facial regions such as eyes, lips, nose etc. We propose a scheme for modelling these regions...
Recently in signal processing, data models based on sparsity prior have drawn much attention. Using this prior several state-of-the-art result is produced in the case of image and video processing based applications. Furthermore, learning the model parameters greatly improves the performance of a given application. We have studied the learning of such models in relevant feature space, and applied...
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.