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)
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)
Classifying Remote Sensing Images (RSI) is a hard task. There are automatic approaches whose results normally need to be revised. The identification and polygon extraction tasks usually rely on applying classification strategies that exploit visual aspects related to spectral and texture patterns identified in RSI regions. There are a lot of image(More)
Otávio A. B. Penattia,∗, Fernanda B. Silva, Eduardo Valle, Valerie Gouet-Brunet, Ricardo da S. Torres RECOD Lab, Institute of Computing (IC), University of Campinas (Unicamp) – Av. Albert Einstein, 1251, Campinas, SP, 13083-852, Brazil Department of Computer Engineering and Industrial Automation (DCA), School of Electrical and Computer Engineering (FEEC),(More)
This paper proposes a new rotation-invariant and scale-invariant representation for texture image retrieval based on steerable pyramid decomposition. By calculating the mean and standard deviation of decomposed image subbands, the texture feature vectors are extracted. To obtain rotation or scale invariance, the feature elements are aligned by considering(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)