Adaptação da cor da tipografia páginas web para pessoas com deficit na visão da cor

A legibilidade do texto é fundamental à sua leitura, sendo para isso determinante o contraste entre as cores usadas para a tipografia e para o fundo. Ainda que a escolha das cores seja adequada, o contraste pode ser insuficiente quando a tipografia é observada por pessoas com deficit na visão da cor, comprometendo assim a legibilidade. Sendo que é significativa a taxa de incidência do deficit na visão da cor, correntemente conhecido por daltonismo, assim como o índice de utilização da web pela população em geral, onde é frequente a existência de blocos de texto - com recurso à cor para tipografia e para o fundo-, são frequentes as situações em que se torna difícil uma leitura adequada, limitando o acesso à mensagem escrita. Neste contexto, este artigo vem propor um método para melhoria das condições de visualização dos blocos de texto, que passa pela aplicação de um algoritmo de adaptação, que efetua a alteração da cor da tipografia para preto ou para branco, dependendo da forma como a cor de fundo é vista pela daltónico. Dessa forma, é incrementado o contraste e é proporcionada uma integral acessibilidade aos conteúdos tipográficos

Contour Enhancement Algorithm for Improving Visual Perception of Deutan and Protan Dichromats

A variety of recoloring methods has been proposed in the literature to remedy the problem of confusing red-green colors faced by dichromat people (as well by other color-blinded people). The common strategy to mitigate this problem is to remap colors to other colors. But, it is clear this does not guarantee neither the necessary contrast to distinguish the elements of an image, nor the naturalness of colors learnt from past experience of each individual. In other words, the individual’s perceptual learning may not hold under color remapping. With this in mind, we introduce the first algorithm primarily focused on the enhancement of object contours in still images, instead of recoloring the pixels of the regions bounded by such contours. This is particularly adequate to increase contrast in images where we find adjacent regions that are color-indistinguishable from the dichromacy’s point of view.info:eu-repo/semantics/publishedVersio

Contour Enhancement Algorithm for Improving Visual Perception of Deutan and Protan Dichromats

A variety of recoloring methods has been proposed in the literature to remedy the problem of confusing red-green colors faced by dichromat people (as well by other color-blinded people). The common strategy to mitigate this problem is to remap colors to other colors. But, it is clear this does not guarantee neither the necessary contrast to distinguish the elements of an image, nor the naturalness of colors learnt from past experience of each individual. In other words, the individual’s perceptual learning may not hold under color remapping. With this in mind, we introduce the first algorithm primarily focused on the enhancement of object contours in still images, instead of recoloring the pixels of the regions bounded by such contours. This is particularly adequate to increase contrast in images where we find adjacent regions that are color-indistinguishable from the dichromacy’s point of view

An Interactive App for Color Deficient Viewers

Color deficient individuals have trouble seeing color contrasts that could be very apparent to individuals with normal color vision. For example, for some color deficient individuals, red and green apples do not have the striking contrast they have for those with normal color vision, or the abundance of red cherries in a tree is not immediately clear due to a lack of perceived contrast. We present a smartphone app that enables color deficient users to visualize such problematic color contrasts in order to help them with daily tasks. The user interacts with the app through the touchscreen. As the user traces a path around the touchscreen, the colors in the image change continuously via a transform that enhances contrasts that are weak or imperceptible for the user under native viewing conditions. Specifically, we propose a transform that shears the data along lines parallel to the dimension corresponding to the affected cone sensitivity of the user. The amount and direction of shear are controlled by the user'sfinger movement over the touchscreen allowing them to visualize these contrasts. Using the GPU, this simple transformation, consisting of a linear shear and translation, is performed efficiently on each pixel and in real-time with the changing position of the user's finger. The user can use the app to aid daily tasks such as distinguishing between red and green apples or picking out ripe bananas

Value visualization in Product Service Systems preliminary design

Emerging from a study in the European aerospace industry, this paper identifies a gap in the way value-related information is communicated to designers of hardware in the preliminary stages of Product Service System (PSS) design. To fit this gap a Lifecycle Value Representation Approach, named LiVReA, that uses color-coded 3D CAD models to enable value information to be translated into visual features, is presented. Such approach aims at enhancing designers' awareness of the value contribution of an early design concept on the overall PSS offer by complementing requirements-based information with criteria reflecting the fulfillment of customers and system value. The paper details the development of the approach, its underlying rationale, the results of preliminary validation activities and the potential for industrial application in the light of the currently available PSS representation tool

Dispositivos móveis para a percepção cromática em deficientes dicromáticos

The inability of perceive all the color spectrum is a deficiency known as color blindness. Generally, this kind of disease is caused by anomalies in the retinal cells or by their absence. These cells are photoreceptors that show sensitivity to three different spectral light bands. In this thesis specific color blindness type, known as Dichromacy, is treated. The Dichromacy is a color vision defect in which, one of the three basic color mechanisms is lacking or not functioning. It is the most significant colorblindness disease, having in account the incapacity caused and knowing that it affects 3% of the world population. Protanopia, Deuteranopia and Tritanopia are Dichromacy subclasses, each one affecting the perception of one of the tree primary colors. This disease is normally caused by a genetic source and has no treatment, neither based on drugs nor based on surgery. It causes important limitations on the daily tasks execution and can lead to several danger situations. For instance, buying fruits at the supermarket, choosing clothes at the shop or in the traffic identifying the light colors. There are several image processing algorithms that allow minimizing this problem. The used methods are able to remap the original colors, which are not perceived by the color blindness people, to the colors that are recognized by them. This is done trying not modifying the original visual semantic. The most important methods that are able to perform those transformations will be presented and discussed in this thesis, especially in what concerns to their advantages and disadvantages to the image recognition by the color blind person. Beyond the algorithms, a practical approach to the use of those techniques in mobile devices is showed. Their ability to capture images (e.g. phone devices) can improve the everyday life of the color blindness people and enrich their perception of reality. The Human visual system is a very complex functional structure. From the retinal eye cells to the visual cortex layers one can find a large number of physical phenomena contributing to the performance of this mechanism. This fact makes the image processing tasks demand for large computational power. The usually methods are able to map the pixels of the original image to the corrected image concerning the color blindness spectral range. This process is supported by an optimization task that allows keeping the visual semantic and, at the same time, increases the number of perceived regions. However, these methods do not consider the spatial relation among the color pixels, but only the relation among the color pixels values. This fact, in some images, leads to an incorrect mapping, joining some regions that are separated in the original image. The process presented in this thesis pretends to overcome this issue increasing the number of visual situations that this type of algorithms is able to treat. The method is based on a texture analysis process to demarcate the different colors of an image, thereby ensuring that the mappings are not made to existing colors in the original image, which are belonging to adjoining regions. Estamos tão acostumados ao nosso sistema visual que raramente nos apercebemos da complexidade envolvida numa simples tarefa como abrir os olhos e visualizar o que nos rodeia. Apesar de usarmos este sentido todos os dias, a visão é na realidade um fenómeno bastante complicado e o olho é provavelmente um dos órgãos mais complexos do corpo humano. Estudos recentes indicam que cerca de 8% da população europeia apresenta anomalias ao nível de algumas das células (cones) da retina. A nossa ferramenta primária de visão são os olhos, são eles também um instrumento biológico de captura que, como uma simples câmara fotográfica, recolhe, foca e processa a luz. A incapacidade do processo visual diferenciar todas ou algumas cores é denominada de daltonismo; a ausência de um grupo de cones sensíveis aos três comprimentos de onda (Longo, Médio e Curto) é chamado de dicromância e pode apresentar-se sob a forma de protanopia, deuteranopia e tritanopia, respectivamente. Esta perturbação tem normalmente origem genética, ocorre mais frequentemente nos indivíduos de sexo masculino, pois está directamente ligado a uma anomalia no cromossoma X. Até à data não existe cura nem com a ajuda de fármacos nem com intervenções cirúrgicas. Torna-se então evidente desenvolver algoritmos (soluções) e implementá-los em mecanismos que possam melhorar o dia-a-dia destas pessoas. A forte penetração de dispositivos móveis (p.e. telemóveis, PDAs) nos mercados mundiais, equipados com sistemas de captação de vídeo e imagem e com processadores mais rápidos, fazem deles uma opção estratégica, pois acompanham, também eles, as pessoas no seu quotidiano. As tentativas de aumentar a complexidade e o desempenho funcional dos algoritmos de correcção daltónica deparam-se com as limitações ao nível da sua implementação física, este problema agrava-se quando implementados em dispositivos móveis. A dissertação actual apresenta dois métodos de correcção de imagens para deficientes de percepção da cor, no âmbito do processamento de imagens, que permitem, por um lado, manter as cores naturais da imagem original e, por outro lado, tornar perceptíveis as cores que são confundidas. No primeiro método, recorrendo ao algoritmo proposto por Giovane R. Kuhn em 2008, são usados processos de quantização da imagem original e recorre posteriormente a analogias físicas (mass-spring) para manter a distância original entre as cores. No segundo método é sugerido um processo de análise de textura para demarcar as diferentes regiões de uma imagem garantindo assim que os mapeamentos não serão feitos para cores, espacialmente adjacentes, já existentes na imagem original

An efficient naturalness-preserving image-recoloring method for dichromats

We present an efficient and automatic image-recoloring technique for dichromats that highlights important visual details that would otherwise be unnoticed by these individuals. While previous techniques approach this problem by potentially changing all colors of the original image, causing their results to look unnatural to color vision deficients, our approach preserves, as much as possible, the image’s original colors. Our approach is about three orders of magnitude faster than previous ones. The results of a paired-comparison evaluation carried out with fourteen color-vision deficients (CVDs) indicated the preference of our technique over the state-of-the-art automatic recoloring technique for dichromats. When considering information visualization examples, the subjects tend to prefer our results over the original images. An extension of our technique that exaggerates color contrast tends to be preferred when CVDs compared pairs of scientific visualization images. These results provide valuable information for guiding the design of visualizations for color-vision deficients

An efficient naturalness-preserving image-recoloring method for dichromats

We present an efficient and automatic image-recoloring technique for dichromats that highlights important visual details that would otherwise be unnoticed by these individuals. While previous techniques approach this problem by potentially changing all colors of the original image, causing their results to look unnatural to color vision deficients, our approach preserves, as much as possible, the image’s original colors. Our approach is about three orders of magnitude faster than previous ones. The results of a paired-comparison evaluation carried out with fourteen color-vision deficients (CVDs) indicated the preference of our technique over the state-of-the-art automatic recoloring technique for dichromats. When considering information visualization examples, the subjects tend to prefer our results over the original images. An extension of our technique that exaggerates color contrast tends to be preferred when CVDs compared pairs of scientific visualization images. These results provide valuable information for guiding the design of visualizations for color-vision deficients