Ricardo da Silva Torres

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Advances in data storage and image acquisition technologies have enabled the creation of large image datasets. In this scenario, it is necessary to develop appropriate information systems to efficiently manage these collections. The commonest approaches use the so-called Content-Based Image Retrieval (CBIR) systems. Basically, these systems try to retrieve(More)
The effectiveness of CBIR systems can be improved by combining image features or by weighting image similarities, as computed from multiple feature vectors. However, feature combination without using similarity functions does not always make sense and the combined similarity function may have to be more complex than weight-based functions in order to(More)
This paper presents two shape descriptors, multiscale fractal dimension and contour saliences, using a graph-based approach— the image foresting transform. It introduces a robust approach to locate contour saliences from the relation between contour and skeleton. The contour salience descriptor consists of a vector, with salience location and value along(More)
Content-Based Image Retrieval (CBIR) presents several challenges and has been subject to extensive research from many domains, such as image processing or database systems. Database researchers are concerned with indexing and querying, whereas image processing experts worry about extracting appropriate image descriptors. Comparatively little work has been(More)
This work exploits the resemblance between content-based image retrieval and image analysis with respect to the design of image descriptors and their effectiveness. In this context, two shape descriptors are proposed: contour saliences and segment saliences. Contour saliences revisits its original definition, where the location of concave points was a(More)
This paper presents an interactive technique for remote sensing image classification. In our proposal, users are able to interact with the classification system, indicating regions of interest (and those which are not). This feedback information is employed by a genetic programming approach to learn user preferences and combine image region descriptors that(More)
This paper discusses ongoing research on scientific workflows at the Institute of Computing, University of Campinas (IC - UNICAMP) Brazil. Our projects with bio-scientists have led us to develop a scientific workflow infrastructure named WOODSS. This framework has two main objectives in mind: to help scientists to specify and annotate their models and(More)
In this paper, we propose a novel framework using <i>Genetic Programming</i> to combine image database descriptors for content-based image retrieval (CBIR). Our framework is validated through several experiments involving two image databases and specific domains, where the images are retrieved based on the shape of their objects.