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

Live Video and Image Recolouring for Colour Vision Deficient Patients

Colour Vision Deficiency (CVD) is an important issue for a significant population across the globe. There are several types of CVD\u27s, such as monochromacy, dichromacy, trichromacy, and anomalous trichromacy. Each of these categories contain specific other subtypes. The aim of this research is to device a scheme to address CVD by using variations in pixel plotting of colours to capture colour disparities and perform colour compensation. The proposed scheme recolours the video and images by colour contrast variation of each colour for CVD patients, and depending on the type of deficiency, it is able to provide live results. Different types of CVD’s can be identified and cured by changing the particular colour related to it and based upon the type of diseases, it performs RGB (Red, Green, and Blue) to LMS (Long, Medium, and Short) transformation. This helps in colour identification and also adjustments of colour contrasts. The processing and rendering of recoloured video and images, allows the affected patients with CVD to see perfect shades in the recoloured frames of video or images and other modes of files. In this thesis, we propose an efficient recolouring algorithm with a strong focus on real-time applications that is capable of providing different recoloured outputs based on specific types of CVD

Colorimetry and Dichromatic Vision

Normal trichromats have three types of cone photoreceptors: L, M, and S cones (most sensitive to long, medium, or short wavelengths, respectively). Therefore, standard colorimetry is based on three variables (X, Y, Z). Dichromats only have two types of functional cones due to genetic factors. The main consequences are that dichromats (1) confuse colors that can only be discriminated by the response of the type of cone they lack and (2) make errors when naming colors. Chromaticity diagrams can be used to specify dichromats’ color confusions. Confusion points represent imaginary stimuli that only activate L, M, or S cones. Confusion lines radiate from confusion points and represent pseudoisochromatic stimuli (i.e., colors confused by the corresponding type of dichromat if presented at an appropriate intensity). Dichromat’s color appearance models have been developed to simulate the colors supposedly seen by dichromats, and there exist color simulation tools that implement some of those models

An Improved Dynamic Daltonization for Color-Blinds

Color-blindness is an inherited condition which leads to the sufferer not being able to distinguish between certain colors. One of the most widely used algorithms for enhancing a color-blind’s color perception of images is Daltonization. Non-iterative Daltonization leaves the possibility of modifying imperceptible colors into colors that already exist in an image. Iterative Daltonization method provides better results by overcoming this problem. This paper presents a new iterative Daltonization method for protanopes which uses hue to ensure imperceptible colors are not modified into colors similar to existing perceptible ones. Experimental results show that the proposed method outperforms similar existing methods

Recoloração de imagens para dicromatas baseada em mapas elásticos

TCC(graduação) - Universidade Federal de Santa Catarina. Campus Araranguá. Engenharia da Computação.A deficiência na percepção de cores (DPC) afeta 8% da população caucasiana masculina, causada pela falha ou ausência de células fotorreceptoras do tipo cone na retina, e proveniente de causa genética, alguma lesão no olho, ou também devido a outras doenças, como diabetes, leucemia, etc. O indivíduo com DPC tem dificuldades na percepção de cores, que variam dependendo do tipo de deficiência. Dicromatas são os indivíduos com DPC causada pela ausência de um dos tipos de fotorreceptores cone, causando dificuldades na percepção das cores. A DPC causa dificuldades na realização de tarefas que necessitam da distinção de cores, o que pode prejudicar o indivíduo tanto na vida pessoal quanto profissional. Este trabalho propõe uma técnica de recoloração de imagens para dicromatas baseada na técnica de redução de dimensionalidade Mapas Elásticos, onde o objetivo é proporcionar aos indivíduos imagens que preservam detalhes da imagem original, como contrastes entre cores, os quais, os dicromatas não percebem. A técnica foi implementada tanto para CPU como para GPU, apresentando bons tempos de execução, além de apresentar bons resultados no aspecto da preservação de contrastes após a recoloração, a técnica também se propõe a preservar o aspecto de naturalidade da imagem, escolhendo o mapeamento final que minimiza a soma total das distância entre a cor original e o mapeamento dela no plano de percepção dos dicromatas.Color Vision Deficiency (CVD) affects 8% of caucasian male populations, caused by failure or absence of cone-like photorreceptor cells in the retina. CVD may be from genetic cause, some eye injury, or from other diseases such as diabetes, leukemia, etc. Individuals with CVD have difficulty in color perception, whose variation depends on the type of disability. Dichromats are individuals with CVD caused by the abscence of one of the types of cone photoreceptors, causing difficulties in the perception of colors. CVD causes difficulties in performing tasks that require color distinction, which can harm the individual in both personal and professional life. This work proposes an image recoloring technique for dichromats based on the Elastic Maps dimensionality reduction technique, where the objective is to provide images that preserve details of the original image, such as color contrasts. The technique was implemented both CPU and GPU, presenting good execution times, and good results in the aspect of preservation of contrasts after recoloring, the technique also proposes to preserve the aspect of naturality of image, choosing the final mapping that minimizes the total sum of the distance between the original color and the mapping of it in the plane of dichromat perception

Computer-Based Solutions to Support Those With Colour Vision Deficiency to Access Day-to-Day Information

In modern-day society, we are bombarded with vast amounts of electronic information which we may be expected to make decisions from. Many people have difficulties in interpreting such information due to either physical or cognitive difficulties in using electronic devices, or an inability to identify information as intended by the author. Colour Vision Deficiency (CVD) is one such problem that can cause considerable difficulty in the interpretation of diagrammatical information. This is because a Colour Vision Deficient (CVDt) person has difficulty in seeing: colour boundaries, different shades of colour and different hues. There has been some research to aid the CVDt, where the majority of the research in image processing changes or transforms colours in any given image. Such transformations use a number of different algorithms to create a CVDt friendly post-processed image from the pre-processed image. A major problem of current transformation algorithms is that they are aimed for specific contexts and cannot be used in generic contexts. For example, the transformation algorithm may be aimed at aiding the CVDt to view postprocessed images of weather maps only. The aim of this dissertation is to provide an improved post-processed image algorithm. The algorithm is intended to provide the CVDt with greater benefit by being able to interpret the information in the post-processed image correctly. The algorithm used in this dissertation is not a colour transformation algorithm instead it is a colour separation algorithm. This concept of colour separation is novel. The colour separation algorithm, which is called the Halo-Effect Algorithm (HEA), parses a given image row-by-row and pixel-by-pixel until the end of file-marker is reached and a CVDt friendly post-processed image is furnished. When there is a colour change between two identified pixels then a colour boundary has been identified within the pre-processed image and a differently coloured pixel is inserted between two, furnishing the post-processed image. As the pre-processed image is parsed row-by-row then the colour the boundary builds up to form a colour boundary interface where the different coloured pixel are inserted in the post-processed image. In this dissertation the separation pixel is always white. The build-up of inserted white pixels at the colour boundary interface of the pre-processed image produces a halo like effect in the post-processed image which is CVDt friendly. To demonstrate the efficacy of the colour separation concept, the HEA has been developed and implemented. A number of surveys have been conducted using participant responses to questions within each survey. The responses that each participant gave were then collated and analysed statistically. Two statistical techniques were used to test a number of hypotheses around the mean of a sample drawn from a normally distributed population. In this dissertation the normally distributed populations were the survey participants. From the analyses of the responses, the survey population was divided into two groups. One group was identified to have no problem with identification of pre-processed colour boundaries and were called the non-CVDt. A second group was identified to be those who had some problems with the identification of pre-processed colour boundaries and were called the indicative- CVDt. Responses from the two groups were collated and statistical analyses were then conducted to test the significance of any results obtained and also to test the validity of the algorithms under investigation. In this dissertation two currently available, but different, colour transformation algorithms were compared with the colour separation algorithm of the HEA. Each of the two transformation algorithms were originally intended for specific use. One was aimed for spectra maps and the other was aimed for background text. Statistical analyses showed that each of the transformation algorithms provided benefit to the indicative-CVDt for their specific context only. However, statistical analyses also showed that HEA fared well in each of the two specific contexts. Thus, hinting that colour separation of HEA could be used in more general contexts. To confirm that colour separation can provide greater benefit to the indicative-CVDt in more generic contexts than colour transformations further surveys were undertaken. In each survey participants were asked a number of questions about a given image where colour boundaries are expected to occur frequently. One was a map of the provinces of Australia and the other a number of differently coloured geometric shapes. Statistical analyses showed that the colour separation algorithm of HEA provided greater benefit to the indicative-CVDt than the two colour transformation algorithms in both cases. Hence, confirming that colour separation of HEA is beneficial to the indicative-CVDt in generic contexts. Colour separation of the HEA is still in its infancy and a great deal more research is required to determine how great its efficacy is. For example, clinical studies could be undertaken using two sets from one population. One set of participants who would have been diagnosed as non-CVDt, which would be identified as a control group, and a second set who would have been diagnosed as CVDt, which would be identified as a test set

Adaptive Methods for Color Vision Impaired Users

Color plays a key role in the understanding of the information in computer environments. It happens that about 5% of the world population is affected by color vision deficiency (CVD), also called color blindness. This visual impairment hampers the color perception, ending up by limiting the overall perception that CVD people have about the surrounding environment, no matter it is real or virtual. In fact, a CVD individual may not distinguish between two different colors, what often originates confusion or a biased understanding of the reality, including web environments, whose web pages are plenty of media elements like text, still images, video, sprites, and so on. Aware of the difficulties that color-blind people may face in interpreting colored contents, a significant number of recoloring algorithms have been proposed in the literature with the purpose of improving the visual perception of those people somehow. However, most of those algorithms lack a systematic study of subjective assessment, what undermines their validity, not to say usefulness. Thus, in the sequel of the research work behind this Ph.D. thesis, the central question that needs to be answered is whether recoloring algorithms are of any usefulness and help for colorblind people or not. With this in mind, we conceived a few preliminary recoloring algorithms that were published in conference proceedings elsewhere. Except the algorithm detailed in Chapter 3, these conference algorithms are not described in this thesis, though they have been important to engender those presented here. The first algorithm (Chapter 3) was designed and implemented for people with dichromacy to improve their color perception. The idea is to project the reddish hues onto other hues that are perceived more regularly by dichromat people. The second algorithm (Chapter 4) is also intended for people with dichromacy to improve their perception of color, but its applicability covers the adaptation of text and image, in HTML5- compliant web environments. This enhancement of color contrast of text and imaging in web pages is done while keeping the naturalness of color as much as possible. Also, to the best of our knowledge, this is the first web recoloring approach targeted to dichromat people that takes into consideration both text and image recoloring in an integrated manner. The third algorithm (Chapter 5) primarily focuses on the enhancement of some of the object contours in still images, instead of recoloring the pixels of the regions bounded by such contours. Enhancing contours is particularly suited to increase contrast in images, where we find adjacent regions that are color indistinguishable from dichromat’s point of view. To our best knowledge, this is one of the first algorithms that take advantage of image analysis and processing techniques for region contours. After accurate subjective assessment studies for color-blind people, we concluded that the CVD adaptation methods are useful in general. Nevertheless, each method is not efficient enough to adapt all sorts of images, that is, the adequacy of each method depends on the type of image (photo-images, graphical representations, etc.). Furthermore, we noted that the experience-based perceptual learning of colorblind people throughout their lives determines their visual perception. That is, color adaptation algorithms must satisfy requirements such as color naturalness and consistency, to ensure that dichromat people improve their visual perception without artifacts. On the other hand, CVD adaptation algorithms should be object-oriented, instead of pixel-oriented (as typically done), to select judiciously pixels that should be adapted. This perspective opens an opportunity window for future research in color accessibility in the field of in human-computer interaction (HCI).A cor desempenha um papel fundamental na compreensão da informação em ambientes computacionais. Porém, cerca de 5% da população mundial é afetada pela deficiência de visão de cor (ou Color Vision Deficiency (CVD), do Inglês), correntemente designada por daltonismo. Esta insuficiência visual dificulta a perceção das cores, o que limita a perceção geral que os indivíduos têm sobre o meio, seja real ou virtual. Efetivamente, um indivíduo com CVD vê como iguais cores que são diferentes, o que origina confusão ou uma compreensão distorcida da realidade, assim como dos ambientes web, onde existe uma abundância de conteúdos média coloridos, como texto, imagens fixas e vídeo, entre outros. Com o intuito de mitigar as dificuldades que as pessoas com CVD enfrentam na interpretação de conteúdos coloridos, tem sido proposto na literatura um número significativo de algoritmos de recoloração, que têm como o objetivo melhorar, de alguma forma, a perceção visual de pessoas com CVD. Porém, a maioria desses trabalhos carece de um estudo sistemático de avaliação subjetiva, o que põe em causa a sua validação, se não mesmo a sua utilidade. Assim, a principal questão à qual se pretende responder, como resultado do trabalho de investigação subjacente a esta tese de doutoramento, é se os algoritmos de recoloração têm ou não uma real utilidade, constituindo assim uma ajuda efetiva às pessoas com daltonismo. Tendo em mente esta questão, concebemos alguns algoritmos de recoloração preliminares que foram publicados em atas de conferências. Com exceção do algoritmo descrito no Capítulo 3, esses algoritmos não são descritos nesta tese, não obstante a sua importância na conceção daqueles descritos nesta dissertação. O primeiro algoritmo (Capítulo 3) foi projetado e implementado para pessoas com dicromacia, a fim de melhorar a sua perceção da cor. A ideia consiste em projetar as cores de matiz avermelhada em matizes que são melhor percebidos pelas pessoas com os tipos de daltonismo em causa. O segundo algoritmo (Capítulo 4) também se destina a melhorar a perceção da cor por parte de pessoas com dicromacia, porém a sua aplicabilidade abrange a adaptação de texto e imagem, em ambientes web compatíveis com HTML5. Isto é conseguido através do realce do contraste de cores em blocos de texto e em imagens, em páginas da web, mantendo a naturalidade da cor tanto quanto possível. Além disso, tanto quanto sabemos, esta é a primeira abordagem de recoloração em ambiente web para pessoas com dicromacia, que trata o texto e a imagem de forma integrada. O terceiro algoritmo (Capítulo 5) centra-se principalmente na melhoria de alguns dos contornos de objetos em imagens, em vez de aplicar a recoloração aos pixels das regiões delimitadas por esses contornos. Esta abordagem é particularmente adequada para aumentar o contraste em imagens, quando existem regiões adjacentes que são de cor indistinguível sob a perspetiva dos observadores com dicromacia. Também neste caso, e tanto quanto é do nosso conhecimento, este é um dos primeiros algoritmos em que se recorre a técnicas de análise e processamento de contornos de regiões. Após rigorosos estudos de avaliação subjetiva com pessoas com daltonismo, concluiu-se que os métodos de adaptação CVD são úteis em geral. No entanto, cada método não é suficientemente eficiente para todos os tipo de imagens, isto é, o desempenho de cada método depende do tipo de imagem (fotografias, representações gráficas, etc.). Além disso, notámos que a aprendizagem perceptual baseada na experiência das pessoas daltónicas ao longo de suas vidas é determinante para perceber aquilo que vêem. Isto significa que os algoritmos de adaptação de cor devem satisfazer requisitos tais como a naturalidade e a consistência da cor, de modo a não pôr em causa aquilo que os destinatários consideram razoável ver no mundo real. Por outro lado, a abordagem seguida na adaptação CVD deve ser orientada aos objetos, em vez de ser orientada aos pixéis (como tem sido feito até ao momento), de forma a possibilitar uma seleção mais criteriosa dos pixéis que deverão ser sujeitos ao processo de adaptação. Esta perspectiva abre uma janela de oportunidade para futura investigação em acessibilidade da cor no domínio da interacção humano-computador (HCI)

Recoloração de imagens para dicromatas baseada em mapas elásticos

TCC(graduação) - Universidade Federal de Santa Catarina. Campus Araranguá. Engenharia da Computação.A deficiência na percepção de cores (DPC) afeta 8% da população caucasiana masculina, causada pela falha ou ausência de células fotorreceptoras do tipo cone na retina, e proveniente de causa genética, alguma lesão no olho, ou também devido a outras doenças, como diabetes, leucemia, etc. O indivíduo com DPC tem dificuldades na percepção de cores, que variam dependendo do tipo de deficiência. Dicromatas são os indivíduos com DPC causada pela ausência de um dos tipos de fotorreceptores cone, causando dificuldades na percepção das cores. A DPC causa dificuldades na realização de tarefas que necessitam da distinção de cores, o que pode prejudicar o indivíduo tanto na vida pessoal quanto profissional. Este trabalho propõe uma técnica de recoloração de imagens para dicromatas baseada na técnica de redução de dimensionalidade Mapas Elásticos, onde o objetivo é proporcionar aos indivíduos imagens que preservam detalhes da imagem original, como contrastes entre cores, os quais, os dicromatas não percebem. A técnica foi implementada tanto para CPU como para GPU, apresentando bons tempos de execução, além de apresentar bons resultados no aspecto da preservação de contrastes após a recoloração, a técnica também se propõe a preservar o aspecto de naturalidade da imagem, escolhendo o mapeamento final que minimiza a soma total das distância entre a cor original e o mapeamento dela no plano de percepção dos dicromatas.Color Vision Deficiency (CVD) affects 8% of caucasian male populations, caused by failure or absence of cone-like photorreceptor cells in the retina. CVD may be from genetic cause, some eye injury, or from other diseases such as diabetes, leukemia, etc. Individuals with CVD have difficulty in color perception, whose variation depends on the type of disability. Dichromats are individuals with CVD caused by the abscence of one of the types of cone photoreceptors, causing difficulties in the perception of colors. CVD causes difficulties in performing tasks that require color distinction, which can harm the individual in both personal and professional life. This work proposes an image recoloring technique for dichromats based on the Elastic Maps dimensionality reduction technique, where the objective is to provide images that preserve details of the original image, such as color contrasts. The technique was implemented both CPU and GPU, presenting good execution times, and good results in the aspect of preservation of contrasts after recoloring, the technique also proposes to preserve the aspect of naturality of image, choosing the final mapping that minimizes the total sum of the distance between the original color and the mapping of it in the plane of dichromat perception