Search results for "COLOR"

Maniquí blanc-i-negre = Capuchino bicolor

Altres noms vulgars: Black-and-white munia (Anglès), Capucin bicolore (Francès), Glanzelsterchen (Alemany) Gabinet de Vertebrats (Departament de Zoologia), Facultat de Ciències Biològiques (Campus de Burjassot), C/ Doctor Moliner, s/n, Bloque B. 5é plant, Burjassot (Valencia). Armari: 24-2 Valencia _

Evaluación de las alteraciones psicológicas y de la calidad de vida en pacientes con cáncer colorrectal localizado

2015

En los países desarrollados y en la mayoría del mundo industrializado, el cáncer constituye uno de los mayores problemas de salud siendo una de las enfermedades más prevalentes. En la actualidad, la estimación en España sobre incidencia resalta que el cáncer más frecuente teniendo en cuenta ambos sexos, con una previsión a 5 años, es el cáncer colorrectal. El principal factor pronóstico es el estadio clínico en el momento de la cirugía, pero en los últimos años se han desarrollado diversos programas de tratamiento adyuvante con quimioterapia y radioterapia para el cáncer colorrectal. Un 70% de estos tumores son de localización proximal (colon), mientras que el resto son distales (recto). Es…

Supporting Autonomous Navigation of Visually Impaired People for Experiencing Cultural Heritage

2020

In this chapter, we present a system for indoor and outdoor localization and navigation to allow the low vision users in experiencing cultural heritage in autonomy. The system is based on the joint utilization of dead-reckoning and computer vision techniques on a smartphone-centric tracking system. The system is explicitly designed for visually impaired people, but it can be easily generalized to other users, and it is built under the assumption that special reference signals, such as colored tapes, painted lines, or tactile paving, are deployed in the environment for guiding visually impaired users along pre-defined paths. Differently from previous works on localization, which are focused …

Optimizing colormaps with consideration for color vision deficiency to enable accurate interpretation of scientific data

2018

Color vision deficiency (CVD) affects more than 4% of the population and leads to a different visual perception of colors. Though this has been known for decades, colormaps with many colors across the visual spectra are often used to represent data, leading to the potential for misinterpretation or difficulty with interpretation by someone with this deficiency. Until the creation of the module presented here, there were no colormaps mathematically optimized for CVD using modern color appearance models. While there have been some attempts to make aesthetically pleasing or subjectively tolerable colormaps for those with CVD, our goal was to make optimized colormaps for the most accurate perce…

Color image quality assessment measure using multivariate generalized Gaussian distribution

2014

This paper deals with color image quality assessment in the reduced-reference framework based on natural scenes statistics. In this context, we propose to model the statistics of the steer able pyramid coefficients by a Multivariate Generalized Gaussian distribution (MGGD). This model allows taking into account the high correlation between the components of the RGB color space. For each selected scale and orientation, we extract a parameter matrix from the three color components sub bands. In order to quantify the visual degradation, we use a closed-form of Kullback-Leibler Divergence (KLD) between two MGGDs. Using "TID 2008" benchmark, the proposed measure has been compared with the most i…

On color image quality assessment using natural image statistics

2014

Color distortion can introduce a significant damage in visual quality perception, however, most of existing reduced-reference quality measures are designed for gray scale images. In this paper, we consider a basic extension of well-known image-statistics based quality assessment measures to color images. In order to evaluate the impact of color information on the measures efficiency, two color spaces are investigated: RGB and CIELAB. Results of an extensive evaluation using TID 2013 benchmark demonstrates that significant improvement can be achieved for a great number of distortion type when the CIELAB color representation is used.

Nonlinearities and Adaptation of Color Vision from Sequential Principal Curves Analysis

2016

Mechanisms of human color vision are characterized by two phenomenological aspects: the system is nonlinear and adaptive to changing environments. Conventional attempts to derive these features from statistics use separate arguments for each aspect. The few statistical explanations that do consider both phenomena simultaneously follow parametric formulations based on empirical models. Therefore, it may be argued that the behavior does not come directly from the color statistics but from the convenient functional form adopted. In addition, many times the whole statistical analysis is based on simplified databases that disregard relevant physical effects in the input signal, as, for instance…

Retrieval of Case 2 Water Quality Parameters with Machine Learning

2018

Water quality parameters are derived applying several machine learning regression methods on the Case2eXtreme dataset (C2X). The used data are based on Hydrolight in-water radiative transfer simulations at Sentinel-3 OLCI wavebands, and the application is done exclusively for absorbing waters with high concentrations of coloured dissolved organic matter (CDOM). The regression approaches are: regularized linear, random forest, Kernel ridge, Gaussian process and support vector regressors. The validation is made with and an independent simulation dataset. A comparison with the OLCI Neural Network Swarm (ONSS) is made as well. The best approached is applied to a sample scene and compared with t…

Retrieval of coloured dissolved organic matter with machine learning methods

2017

The coloured dissolved organic matter (CDOM) concentration is the standard measure of humic substance in natural waters. CDOM measurements by remote sensing is calculated using the absorption coefficient (a) at a certain wavelength (e.g. 440nm). This paper presents a comparison of four machine learning methods for the retrieval of CDOM from remote sensing signals: regularized linear regression (RLR), random forest (RF), kernel ridge regression (KRR) and Gaussian process regression (GPR). Results are compared with the established polynomial regression algorithms. RLR is revealed as the simplest and most efficient method, followed closely by its nonlinear counterpart KRR.

Road scenes analysis in adverse weather conditions by polarization-encoded images and adapted deep learning

2019

International audience; Object detection in road scenes is necessary to develop both autonomous vehicles and driving assistance systems. Even if deep neural networks for recognition task have shown great performances using conventional images, they fail to detect objects in road scenes in complex acquisition situations. In contrast, polarization images, characterizing the light wave, can robustly describe important physical properties of the object even under poor illumination or strong reflections. This paper shows how non-conventional polarimetric imaging modality overcomes the classical methods for object detection especially in adverse weather conditions. The efficiency of the proposed …