Search results for "artificial intelligence"

Content Based Indexing of Image and Video Databases by Global and Shape Features

1996

Indexing and retrieval methods based on the image content are required to effectively use information from the large repositories of digital images and videos currently available. Both global (colour, texture, motion, etc.) and local (object shape, etc.) features are needed to perform a reliable content based retrieval. We present a method for automatic extraction of global image features, like colour and motion parameters, and their use for data restriction in video database querying. Further retrieval is therefore accomplished, in a restricted set of images, by shape feature (skeleton, local symmetry moments, correlation, etc.) local search. The proposed indexing methodology has been deve…

A memetic approach to discrete tomography from noisy projections

2010

Discrete tomography deals with the reconstruction of images from very few projections, which is, in the general case, an NP-hard problem. This paper describes a new memetic reconstruction algorithm. It generates a set of initial images by network flows, related to two of the input projections, and lets them evolve towards a possible solution, by using crossover and mutation. Switch and compactness operators improve the quality of the reconstructed images during each generation, while the selection of the best images addresses the evolution to an optimal result. One of the most important issues in discrete tomography is known as the stability problem and it is tackled here, in the case of no…

Analysis of Users Behaviour from a Movie Preferences Perspective

2018

Despite their tremendous popularity, Online Social Networks (OSNs) have several issues related to the privacy of social users. These issues have motivated researchers to develop OSN services that take advantage of the decentralized platforms (such as P2P systems or opportunistic networks). Decentralized Online Social Networks (DOSNs) need specific approaches to manage the decentralization of social data. In particular, data availability is one of the main issues and current proposals exploit properties of the social relationships to manage it. At the best of our knowledge, there are no proposals which exploit similarity between users, expressed with the term homophily. Homophily has been we…

Exploiting community detection to recommend privacy policies in decentralized online social networks

2018

The usage of Online Social Networks (OSNs) has become a daily activity for billions of people that share their contents and personal information with the other users. Regardless of the platform exploited to provide the OSNs’ services, these contents’ sharing could expose the OSNs’ users to a number of privacy risks if proper privacy-preserving mechanisms are not provided. Indeed, users must be able to define its own privacy policies that are exploited by the OSN to regulate access to the shared contents. To reduce such users’ privacy risks, we propose a Privacy Policies Recommended System (PPRS) that assists the users in defining their own privacy policies. Besides suggesting the most appro…

Algorithmic paradigms for stability-based cluster validity and model selection statistical methods, with applications to microarray data analysis

2012

AbstractThe advent of high throughput technologies, in particular microarrays, for biological research has revived interest in clustering, resulting in a plethora of new clustering algorithms. However, model selection, i.e., the identification of the correct number of clusters in a dataset, has received relatively little attention. Indeed, although central for statistics, its difficulty is also well known. Fortunately, a few novel techniques for model selection, representing a sharp departure from previous ones in statistics, have been proposed and gained prominence for microarray data analysis. Among those, the stability-based methods are the most robust and best performing in terms of pre…

M-VIF: A machine-vision based on information fusion

2002

The authors describe a new architecture for machine vision, which is based on information fusion approach. Its general design has been developed by using a formal computation model that integrates three main ingredients of the visual computation: the data, the models, and the algorithms. The hardware design and the software environment of M-VIF are also given. The simulation of M-VIF is under development on the HERMIA-machine.

Dissimilarity Measures for the Identification of Earthquake Focal Mechanisms

2013

This work presents a study about dissimilarity measures for seismic signals, and their relation to clustering in the particular problem of the identification of earthquake focal mechanisms, i.e. the physical phenomena which have generated an earthquake. Starting from the assumption that waveform similarity implies similarity in the focal parameters, important details about them can be determined by studying waveforms related to the wave field produced by earthquakes and recorded by a seismic network. Focal mechanisms identification is currently investigated by clustering of seismic events, using mainly cross-correlation dissimilarity in conjunction with hierarchical clustering algorithm. By…

Indexed Two-Dimensional String Matching

2016

Restoration of Vertical Line Scratches with a Distributed Genetic Algorithm

2006

This contribution approaches the problem of scratch restoration in old movies as a optimisation's problem. The functional based on the statistical properties of the image around the scratch is optimised using an ad-hoc genetic algorithm. Given the large amount of the computational time needed by genetic algorithms, a network of standard workstations with heterogeneous operating systems has been used. Each workstation in the network works on each scratch to perform the restoration, and a specific machine works as root node with the task of distributing jobs on the network and adding the outputted restored scratches back into the image.

Improving Harris corner selection strategy

2011

This study describes a corner selection strategy based on the Harris approach. Corners are usually defined as interest points for which intensity variation in the principal directions is locally maximised, as response from a filter given by the linear combination of the determinant and the trace of the autocorrelation matrix. The Harris corner detector, in its original definition, is only rotationally invariant, but scale-invariant and affine-covariant extensions have been developed. As one of the main drawbacks, corner detector performances are influenced by two user-given parameters: the linear combination coefficient and the response filter threshold. The main idea of the authors' approa…