Ricardo Dutra da Silva

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Problems such as image classification, object detection and recognition rely on low-level feature descriptors to represent visual information. Several feature extraction methods have been proposed, including the Histograms of Oriented Gradients (HOG), which captures edge information by analyzing the distribution of intensity gradients and their directions.(More)
Tensor scale is a morphometric parameter that unifies the representation of local structure thickness, orientation, and anisotropy, which can be used in several computer vision and image processing tasks. In this paper, we exploit this concept for binary images and propose a shape descriptor that encodes region and contour properties in a very efficient(More)
BACKGROUND Despite worldwide recognition of the burden of dementia, no epidemiological data is yet available in Portugal. The objective of this study is to estimate the prevalence and describe the pattern of cognitive impairment with dementia or no dementia (CIND) in rural and urban populations from Northern Portugal. METHODS Two random samples of(More)
Image denoising is a relevant issue found in diverse image processing and computer vision problems. It is a challenge to preserve important features, such as edges, corners and other sharp structures, during the denoising process. Wavelet transforms have been widely used for image denoising since they provide a suitable basis for separating noisy signal(More)
Processing images of underwater environments of Antarctic lakes is challenging due to poor lighting conditions, low saturation and noise. This paper presents a novel pipeline for dense point cloud scene reconstruction from underwater stereo images and video obtained with low-cost consumer recording hardware. Features in stereo frames are selected and(More)
Image segmentation is a fundamental process in remote sensing applications, whose main purpose is to allow a meaningful discrimination among constituent regions of interest. This work presents a novel image segmentation method based on wavelet transforms for extracting a number of color and texture features from the images. Traditional feature extraction(More)
Traditionally, available route planners suggest paths in terms of streets, although, sidewalks of a same street may present different accessibility conditions for wheelchair users. To address this problem, we describe in this paper a sidewalk-based model for wheelchair route planning. The model is a graph in which vertices are corners that makeup city(More)
A central problem in image processing and computer vision is the computation of corresponding interest points in a given set of images. Usually, interest points are considered as independent elements described by some local information. Due to the limitations of such an approach, many incorrect correspondences can be obtained. A specific contribution of(More)