INTRODUCTION The colored ultrasound images can better highlight the joint echotexture damage. OBJECTIVE To detect echotexture changes in joints of patients with rheumatic diseases, through a color histogram, and to correlate the area measurements with the gray scale (GS). METHODS Four patients with chondrocalcinosis, 5 patients with osteoarthritis and 1 patient with psoriatic arthritis were...

Motivated by the success of Deep Neural Networks in computer vision, we propose a deep Regularized Reconstruction Independent Component Analysis network (RICA) for RGB-D image classification. In each layer of this network, we include a RICA as the basic building block to determine the relationship between the gray-scale and depth images corresponding to the same object or scene. Implementing co...

This paper investigates Y UV -to-RGB color space conversion on FPGA-augmented TriMedia-32 processor. First, we outline the extension of TriMedia-32 architecture consisting of FPGA-based Reconfigurable Functional Units (RFU) and associated generic instructions. Then we analyse a YUV-RGB (RFU–specific) instruction which can process four pixels per call, and propose a scheme to implement the YUV-R...

The use of color in image processing is motivated by two principal factors; First color is a powerful descriptor that often simplifies object identification and extraction from a scene. Second, human can discern thousands of color shades and intensities, compared to about only two dozen shades of gray. In RGB model, each color appears in its primary spectral components of red, green and blue. T...

Bilinear Heterogeneous Information Machine for RGB-D Action Recognition Report Title This paper proposes a novel approach to action recognition from RGB-D cameras, in which depth features and RGB visual features are jointly used. Rich heterogeneous RGB and depth data are effectively compressed and projected to a learned shared space, in order to reduce noise and capture useful information for r...

In this paper we propose a challenging new computer vision task of inferring Bread Units (BUs) from food images. Assessing nutritional information and nutrient volume from a meal is an important task for diabetes patients. At the moment, diabetes patients learn the assessment of BUs on a scale of one to ten, by learning correspondence of BU and meals from textbooks. We introduce a large scale d...

The present study considers a fuzzy color system in which three membership functions are constructed on the RGB color triangle. This system can process a fuzzy input (as the membership values of subjects) to an RGB system and output the center of gravity of three weights associated with respective grades. Three membership functions are applied to the RGB color triangle relationship. By treating...

In this paper, we present a novel RGB-D SLAM system based on visual odometry and an extended information filter, which does not require any other sensors or odometry. In contrast to the graph optimization approaches, this is more suitable for online applications. A visual dead reckoning algorithm based on visual residuals is devised, which is used to estimate motion control input. In addition, ...

We address the problem of object recognition from RGB-D images using deep convolutional neural networks (CNNs). We advocate the use of 3D CNNs to fully exploit the 3D spatial information in depth images as well as the use of pretrained 2D CNNs to learn features from RGB-D images. There exists currently no large scale dataset available comprising depth information as compared to those for RGB da...