This paper presents a Bayesian Network model for ContentBased Image Retrieval (CBIR). In the explanation and test of this work, only two images features (semantic evidences) are i...
Paulo S. Rodrigues, Gilson A. Giraldi, Ade A. Arau...
Information retrieval techniques have to face both the growing amount of data to be processed and the "natural" distribution of these data over the network. Hence, we in...
This paper addresses automatic image annotation problem and its application to multi-modal image retrieval. The contribution of our work is three-fold. (1) We propose a probabilis...
The variety of features available to represent multimedia data constitutes a rich pool of information. However, the plethora of data poses a challenge in terms of feature selectio...
In this paper, we present the main features of VISTO (Vector Image Serach TOol), a new Content-Based Image Retrieval (CBIR) system for vector images. Though unsuitable for photore...
Tania Di Mascio, Daniele Frigioni, Laura Tarantino