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)
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)
This paper discusses inter-robot and human-robot communication by bare hand dynamic gestures. We use a Bag-of-Features and a local part model approach for bare hand dynamic hand gesture recognition from video. We used dense sampling to extract local 3D multiscale whole-part features. We adopted three dimensional histograms of a gradient orientation (3D HOG)(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)
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)
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)
Segmentation in image processing refers to the process of partitioning a digital image into multiple segments. This paper makes an attempt to segment the Comic images for extraction the text. Segmentation of comic images into extract the text is a challenging task primarily because of complexity of the structural Features like color, shape and texture. In(More)
An open-set recognition scenario is the one in which there are no a priori training samples for some classes that might appear during testing. Usually, many applications are inherently open set. Consequently, the successful closed-set solutions in the literature are not always suitable for real-world recognition problems. Here, we propose a novel multiclass(More)