365 research outputs found
Adapting website design for people with color-blindness
The aim of the study is the description of problem of developing web design for people with color blindness. The objectives of the study are familiarising with the exiting algorithms of simulation color blindness and searching the most appropriate color models to realize a filter of disputed colors. The object of the study is the convertation of color models and algorithms of filtration. The subject of the study are methods of recognition disputed colors. In the study were investigated the problems of color blind people, examined the basic concepts of trichromatic color vision theory, substantiated the necessity of changing different types of color models, given formulas convertation from RGB-color model to HSL-color model, systematized the algorithms of imitation and filtration of colors for different types of dichromacy: protanopia, deuteranopia and tritanopia. The results of the study are planned using in development of adapting website design for people with color blindness.Метою дослідження є опис проблеми розробки веб-дизайну для людей з порушеннями кольоросприйняття. Задачами дослідження є ознайомлення з існуючими алгоритмами імітації порушень кольоросприйняття та пошук найбільш відповідних колірних моделей для реалізації фільтрування спірних кольорів. Об’єктом дослідження є конвертація колірних моделей та алгоритм фільтрування. Предметом дослідження є методи визначення спірних кольорів. У статті досліджено проблеми людей із різними видами порушень кольоросприйняття, розглянуто основні положення теорії трикомпонентного зору, обґрунтовано необхідність переходу з одних колірних моделей до інших, наведено формули конвертації з RGB-моделі до HSL-моделі, систематизовано алгоритми імітації та фільтрування кольорів у різних видах дихроматизму: протанопії, дейтеранопії та тританопії. Результати дослідження планується використати при розробці системи адаптації дизайну сайту для людей із порушеннями кольоросприйняття
Segmentation and Characterization of Small Retinal Vessels in Fundus Images Using the Tensor Voting Approach
RÉSUMÉ
La rétine permet de visualiser facilement une partie du réseau vasculaire humain. Elle offre
ainsi un aperçu direct sur le développement et le résultat de certaines maladies liées au réseau
vasculaire dans son entier. Chaque complication visible sur la rétine peut avoir un impact sur
la capacité visuelle du patient. Les plus petits vaisseaux sanguins sont parmi les premières
structures anatomiques affectées par la progression d’une maladie, être capable de les analyser
est donc crucial. Les changements dans l’état, l’aspect, la morphologie, la fonctionnalité, ou
même la croissance des petits vaisseaux indiquent la gravité des maladies.
Le diabète est une maladie métabolique qui affecte des millions de personnes autour
du monde. Cette maladie affecte le taux de glucose dans le sang et cause des changements
pathologiques dans différents organes du corps humain. La rétinopathie diabétique décrit l’en-
semble des conditions et conséquences du diabète au niveau de la rétine. Les petits vaisseaux
jouent un rôle dans le déclenchement, le développement et les conséquences de la rétinopa-
thie. Dans les dernières étapes de cette maladie, la croissance des nouveaux petits vaisseaux,
appelée néovascularisation, présente un risque important de provoquer la cécité. Il est donc
crucial de détecter tous les changements qui ont lieu dans les petits vaisseaux de la rétine
dans le but de caractériser les vaisseaux sains et les vaisseaux anormaux. La caractérisation
en elle-même peut faciliter la détection locale d’une rétinopathie spécifique.
La segmentation automatique des structures anatomiques comme le réseau vasculaire est
une étape cruciale. Ces informations peuvent être fournies à un médecin pour qu’elles soient
considérées lors de son diagnostic. Dans les systèmes automatiques d’aide au diagnostic, le
rôle des petits vaisseaux est significatif. Ne pas réussir à les détecter automatiquement peut
conduire à une sur-segmentation du taux de faux positifs des lésions rouges dans les étapes
ultérieures. Les efforts de recherche se sont concentrés jusqu’à présent sur la localisation
précise des vaisseaux de taille moyenne. Les modèles existants ont beaucoup plus de difficultés
à extraire les petits vaisseaux sanguins. Les modèles existants ne sont pas robustes à la grande
variance d’apparence des vaisseaux ainsi qu’à l’interférence avec l’arrière-plan. Les modèles de
la littérature existante supposent une forme générale qui n’est pas suffisante pour s’adapter
à la largeur étroite et la courbure qui caractérisent les petits vaisseaux sanguins. De plus, le
contraste avec l’arrière-plan dans les régions des petits vaisseaux est très faible. Les méthodes
de segmentation ou de suivi produisent des résultats fragmentés ou discontinus. Par ailleurs,
la segmentation des petits vaisseaux est généralement faite aux dépends de l’amplification
du bruit. Les modèles déformables sont inadéquats pour segmenter les petits vaisseaux. Les
forces utilisées ne sont pas assez flexibles pour compenser le faible contraste, la largeur, et
vii
la variance des vaisseaux. Enfin, les approches de type apprentissage machine nécessitent un
entraînement avec une base de données étiquetée. Il est très difficile d’obtenir ces bases de
données dans le cas des petits vaisseaux.
Cette thèse étend les travaux de recherche antérieurs en fournissant une nouvelle mé-
thode de segmentation des petits vaisseaux rétiniens. La détection de ligne à échelles multiples
(MSLD) est une méthode récente qui démontre une bonne performance de segmentation dans
les images de la rétine, tandis que le vote tensoriel est une méthode proposée pour reconnecter
les pixels. Une approche combinant un algorithme de détection de ligne et de vote tensoriel est
proposée. L’application des détecteurs de lignes a prouvé son efficacité à segmenter les vais-
seaux de tailles moyennes. De plus, les approches d’organisation perceptuelle comme le vote
tensoriel ont démontré une meilleure robustesse en combinant les informations voisines d’une
manière hiérarchique. La méthode de vote tensoriel est plus proche de la perception humain
que d’autres modèles standards. Comme démontré dans ce manuscrit, c’est un outil pour
segmenter les petits vaisseaux plus puissant que les méthodes existantes. Cette combinaison
spécifique nous permet de surmonter les défis de fragmentation éprouvés par les méthodes de
type modèle déformable au niveau des petits vaisseaux. Nous proposons également d’utiliser
un seuil adaptatif sur la réponse de l’algorithme de détection de ligne pour être plus robuste
aux images non-uniformes. Nous illustrons également comment une combinaison des deux
méthodes individuelles, à plusieurs échelles, est capable de reconnecter les vaisseaux sur des
distances variables. Un algorithme de reconstruction des vaisseaux est également proposé.
Cette dernière étape est nécessaire car l’information géométrique complète est requise pour
pouvoir utiliser la segmentation dans un système d’aide au diagnostic.
La segmentation a été validée sur une base de données d’images de fond d’oeil à haute
résolution. Cette base contient des images manifestant une rétinopathie diabétique. La seg-
mentation emploie des mesures de désaccord standards et aussi des mesures basées sur la
perception. En considérant juste les petits vaisseaux dans les images de la base de données,
l’amélioration dans le taux de sensibilité que notre méthode apporte par rapport à la méthode
standard de détection multi-niveaux de lignes est de 6.47%. En utilisant les mesures basées
sur la perception, l’amélioration est de 7.8%.
Dans une seconde partie du manuscrit, nous proposons également une méthode pour
caractériser les rétines saines ou anormales. Certaines images contiennent de la néovascula-
risation. La caractérisation des vaisseaux en bonne santé ou anormale constitue une étape
essentielle pour le développement d’un système d’aide au diagnostic. En plus des défis que
posent les petits vaisseaux sains, les néovaisseaux démontrent eux un degré de complexité
encore plus élevé. Ceux-ci forment en effet des réseaux de vaisseaux à la morphologie com-
plexe et inhabituelle, souvent minces et à fortes courbures. Les travaux existants se limitent
viii
à l’utilisation de caractéristiques de premier ordre extraites des petits vaisseaux segmentés.
Notre contribution est d’utiliser le vote tensoriel pour isoler les jonctions vasculaires et d’uti-
liser ces jonctions comme points d’intérêts. Nous utilisons ensuite une statistique spatiale
de second ordre calculée sur les jonctions pour caractériser les vaisseaux comme étant sains
ou pathologiques. Notre méthode améliore la sensibilité de la caractérisation de 9.09% par
rapport à une méthode de l’état de l’art.
La méthode développée s’est révélée efficace pour la segmentation des vaisseaux réti-
niens. Des tenseurs d’ordre supérieur ainsi que la mise en œuvre d’un vote par tenseur via
un filtrage orientable pourraient être étudiés pour réduire davantage le temps d’exécution et
résoudre les défis encore présents au niveau des jonctions vasculaires. De plus, la caractéri-
sation pourrait être améliorée pour la détection de la rétinopathie proliférative en utilisant
un apprentissage supervisé incluant des cas de rétinopathie diabétique non proliférative ou
d’autres pathologies. Finalement, l’incorporation des méthodes proposées dans des systèmes
d’aide au diagnostic pourrait favoriser le dépistage régulier pour une détection précoce des
rétinopathies et d’autres pathologies oculaires dans le but de réduire la cessité au sein de la
population.----------ABSTRACT
As an easily accessible site for the direct observation of the circulation system, human retina
can offer a unique insight into diseases development or outcome. Retinal vessels are repre-
sentative of the general condition of the whole systematic circulation, and thus can act as
a "window" to the status of the vascular network in the whole body. Each complication on
the retina can have an adverse impact on the patient’s sight. In this direction, small vessels’
relevance is very high as they are among the first anatomical structures that get affected
as diseases progress. Moreover, changes in the small vessels’ state, appearance, morphology,
functionality, or even growth indicate the severity of the diseases.
This thesis will focus on the retinal lesions due to diabetes, a serious metabolic disease
affecting millions of people around the world. This disorder disturbs the natural blood glucose
levels causing various pathophysiological changes in different systems across the human body.
Diabetic retinopathy is the medical term that describes the condition when the fundus and
the retinal vessels are affected by diabetes. As in other diseases, small vessels play a crucial
role in the onset, the development, and the outcome of the retinopathy. More importantly,
at the latest stage, new small vessels, or neovascularizations, growth constitutes a factor of
significant risk for blindness. Therefore, there is a need to detect all the changes that occur
in the small retinal vessels with the aim of characterizing the vessels to healthy or abnormal.
The characterization, in turn, can facilitate the detection of a specific retinopathy locally,
like the sight-threatening proliferative diabetic retinopathy.
Segmentation techniques can automatically isolate important anatomical structures like
the vessels, and provide this information to the physician to assist him in the final decision. In
comprehensive systems for the automatization of DR detection, small vessels role is significant
as missing them early in a CAD pipeline might lead to an increase in the false positive rate
of red lesions in subsequent steps. So far, the efforts have been concentrated mostly on the
accurate localization of the medium range vessels. In contrast, the existing models are weak
in case of the small vessels. The required generalization to adapt an existing model does not
allow the approaches to be flexible, yet robust to compensate for the increased variability in
the appearance as well as the interference with the background. So far, the current template
models (matched filtering, line detection, and morphological processing) assume a general
shape for the vessels that is not enough to approximate the narrow, curved, characteristics
of the small vessels. Additionally, due to the weak contrast in the small vessel regions,
the current segmentation and the tracking methods produce fragmented or discontinued
results. Alternatively, the small vessel segmentation can be accomplished at the expense of
x
background noise magnification, in the case of using thresholding or the image derivatives
methods. Furthermore, the proposed deformable models are not able to propagate a contour
to the full extent of the vasculature in order to enclose all the small vessels. The deformable
model external forces are ineffective to compensate for the low contrast, the low width, the
high variability in the small vessel appearance, as well as the discontinuities. Internal forces,
also, are not able to impose a global shape constraint to the contour that could be able to
approximate the variability in the appearance of the vasculature in different categories of
vessels. Finally, machine learning approaches require the training of a classifier on a labelled
set. Those sets are difficult to be obtained, especially in the case of the smallest vessels. In
the case of the unsupervised methods, the user has to predefine the number of clusters and
perform an effective initialization of the cluster centers in order to converge to the global
minimum.
This dissertation expanded the previous research work and provides a new segmentation
method for the smallest retinal vessels. Multi-scale line detection (MSLD) is a recent method
that demonstrates good segmentation performance in the retinal images, while tensor voting
is a method first proposed for reconnecting pixels. For the first time, we combined the
line detection with the tensor voting framework. The application of the line detectors has
been proved an effective way to segment medium-sized vessels. Additionally, perceptual
organization approaches like tensor voting, demonstrate increased robustness by combining
information coming from the neighborhood in a hierarchical way. Tensor voting is closer than
standard models to the way human perception functions. As we show, it is a more powerful
tool to segment small vessels than the existing methods. This specific combination allows us
to overcome the apparent fragmentation challenge of the template methods at the smallest
vessels. Moreover, we thresholded the line detection response adaptively to compensate for
non-uniform images. We also combined the two individual methods in a multi-scale scheme
in order to reconnect vessels at variable distances. Finally, we reconstructed the vessels
from their extracted centerlines based on pixel painting as complete geometric information
is required to be able to utilize the segmentation in a CAD system.
The segmentation was validated on a high-resolution fundus image database that in-
cludes diabetic retinopathy images of varying stages, using standard discrepancy as well as
perceptual-based measures. When only the smallest vessels are considered, the improve-
ments in the sensitivity rate for the database against the standard multi-scale line detection
method is 6.47%. For the perceptual-based measure, the improvement is 7.8% against the
basic method.
The second objective of the thesis was to implement a method for the characterization of
isolated retinal areas into healthy or abnormal cases. Some of the original images, from which
xi
these patches are extracted, contain neovascularizations. Investigation of image features
for the vessels characterization to healthy or abnormal constitutes an essential step in the
direction of developing CAD system for the automatization of DR screening. Given that the
amount of data will significantly increase under CAD systems, the focus on this category of
vessels can facilitate the referral of sight-threatening cases to early treatment. In addition
to the challenges that small healthy vessels pose, neovessels demonstrate an even higher
degree of complexity as they form networks of convolved, twisted, looped thin vessels. The
existing work is limited to the use of first-order characteristics extracted from the small
segmented vessels that limits the study of patterns. Our contribution is in using the tensor
voting framework to isolate the retinal vascular junctions and in turn using those junctions
as points of interests. Second, we exploited second-order statistics computed on the junction
spatial distribution to characterize the vessels as healthy or neovascularizations. In fact, the
second-order spatial statistics extracted from the junction distribution are combined with
widely used features to improve the characterization sensitivity by 9.09% over the state of
art.
The developed method proved effective for the segmentation of the retinal vessels. Higher
order tensors along with the implementation of tensor voting via steerable filtering could
be employed to further reduce the execution time, and resolve the challenges at vascular
junctions. Moreover, the characterization could be advanced to the detection of prolifera-
tive retinopathy by extending the supervised learning to include non-proliferative diabetic
retinopathy cases or other pathologies. Ultimately, the incorporation of the methods into
CAD systems could facilitate screening for the effective reduction of the vision-threatening
diabetic retinopathy rates, or the early detection of other than ocular pathologies
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)
CVD-MET: an image difference metric designed for analysis of color vision deficiency aids
Color vision deficiency (CVD) has gained in relevance in the last decade, with a
surge of proposals for aid systems that aim to improve the color discrimination capabilities of
CVD subjects. This paper focuses on the proposal of a new metric called CVD-MET, that can
evaluate the efficiency and naturalness of these systems through a set of images using a simulation
of the subject’s vision. In the simulation, the effect of chromatic adaptation is introduced via
CIECAM02, which is relevant for the evaluation of passive aids (color filters). To demonstrate
the potential of the CVD-MET, an evaluation of a representative set of passive and active aids
is carried out both with conventional image quality metrics and with CVD-MET. The results
suggest that the active aids (recoloration algorithms) are in general more efficient and produce
more natural images, although the changes that are introduced do not shift the CVD’s perception
of the scene towards the normal observer’s perception.Junta de Andalucia A-TIC-050-UGR18Spanish Government FIS2017-89258-PMinisterio de Ciencia, Innovación y Universidades RTI2018-094738-B-I0
Character Recognition
Character recognition is one of the pattern recognition technologies that are most widely used in practical applications. This book presents recent advances that are relevant to character recognition, from technical topics such as image processing, feature extraction or classification, to new applications including human-computer interfaces. The goal of this book is to provide a reference source for academic research and for professionals working in the character recognition field
Virtual Reality Games for Motor Rehabilitation
This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion
Renk körlüğünün tanısına yönelik yeni bir arayüz
06.03.2018 tarihli ve 30352 sayılı Resmi Gazetede yayımlanan “Yükseköğretim Kanunu İle Bazı Kanun Ve Kanun Hükmünde Kararnamelerde Değişiklik Yapılması Hakkında Kanun” ile 18.06.2018 tarihli “Lisansüstü Tezlerin Elektronik Ortamda Toplanması, Düzenlenmesi ve Erişime Açılmasına İlişkin Yönerge” gereğince tam metin erişime açılmıştır.Renk körlüğü, özellikle erkek nüfusu arasında yaygın olan bir görme kusurudur. Belirli meslek dallarında çalışma yeterliliği veya bazı belge ve sertifikaların temininde renk körlüğü testinden başarılı olma zorunluluğu bulunmaktadır. Ancak bu testlerin geçerliliği ve doğruluğu büyük bir tartışma konusudur. Günümüzde yaygın olarak kullanılan Ishihara renk körlüğü testi deneklerin renk körü olup olmadıklarını sadece pozitif/negatif anlamında ölçen testler olup yaklaşık yüz yıl önceki teknolojik gelişmişliğe sahiptir. Bununla beraber, renk körlüğü konusunda literatürde yer almış diğer çalışmalarda önerilen birçok test geçersiz ölçüm yöntemi, süre olumsuzlukları veya doğruluklarının yeterli olmaması gibi nedenlerden dolayı Ishihara testi kadar pratik ve yaygın kullanım alanı bulamamaktadırlar. Günümüzde hassasiyet ve görüntü kaliteleri oldukça tatminkâr seviyelere gelen ekranlar ve bu ekranları süren yüksek performanslı donanımlar, hafif-ergonomik kasalar, düşük maliyetler ve gelişmiş bilişim altyapıları sebebiyle kişisel bilgisayarların, dizüstü bilgisayarların veya tabletlerin renk körlüğü testlerinde kullanılmasının teknolojik olarak mümkün hale gelmiştir. Bu tez çalışmasının amacı, renk körlüğünün detaylı tanısına yönelik yeni bir test yazılımının geliştirilmesidir. Geliştirilen yeni test sayesinde mevcut ve yaygın kullanılan renk körlüğü testinde renk paletlerinden ve ortam şartlarından kaynaklanan olumsuzlukların önüne geçilmesi hedeflenmiştir. Ayrıca deneklere uygulanan testler ve bu testlere testin taşınması, çoğaltılması, kullanılması, sonuç verilerinin çok daha kolay saklanması ve bu verilere çok daha kolay erişilmesi hedeflenmiştir. Bu sayede renkli görme kusuru açısından hastalardan elde edilen verilerle analiz çalışmalarının çok daha kolay yürütülmesi amaçlanmıştır. Yeni test dört aşamada gerçekleştirilmiş ve her aşaması denekler üzerinde uygulanmıştır. Çalışma grubu 111 renkli görme kusuru bulunan ve 137 normal renkli görme yetisine sahip, toplam 248 kişiden oluşmaktadır. Ishihara testlerine kıyasen yeni test, deneğin sadece 'renkli görme' yetisinin olup/olmadığının tanısında %100 duyarlılık ve %100 özgüllük elde edilmesinin yanı sıra deneğe hangi renk tonlarına karşı kusurlu olduğunun da yaklaşık olarak gösterilmesi sağlanmıştır. Ayrıca testten elde edilen verilerin bulanık mantık yaklaşımı ile hazırlanan bir algoritmada analiz edilerek deneğin renk körlüğü kusuru olup olmadığının tanısı gerçekleştirilmiştir.ait kişisel veriler bir bilişim ortamında potansiyel araştırma ve analiz işlemlerine uygun olacak şekilde depolanmıştır. Bunun yanı sıra, yeni testin bilgisayar ortamında hazırlanmasıyla, mevcut olan renk körlüğü testlerine nazaranColour-blindness is a vision deficiency that is prevalent on male populations. A successful colour-blindness test score is necessary in some particular professions or obtaining some certificates. However, the validity and accuracy of these tests are controversial. Ishihara colour-blindness tests, which have almost one-century background, are being used widespread to discriminate the subjects whether they have colour deficiency or not as simple as in positive/negative logic. However, the rest of the methods related to colour blindness in the related literature have not been popular since they infer some drawbacks such as invalid test equipment, time-consuming features and inadequate accuracy. Nowadays even personal computers having modern display technologies with high performance hardware, light and ergonomic casings, low cost parts and along with advanced information systems enable colour-blindness tests applying on them feasible. The aim of this thesis is to improve a novel colour-blindness tests which gives a detailed result about the colour that an individual cannot see besides just classifying whether the individual is colour-blind or not. With the benefits of the new test, it has been aimed to preclude that the flaws inflicted by colour plates commonly used and ambient light. All the results and demographic information gathered from the individuals have been properly stored for further studies and analyses. Additionally, the new test, developed as a computer-based test compared to conventional tests, became more portable, easier to use and has many advantageous over others especially when data storage and analysis capabilities are concerned. The new test has designed in four phase and all the phases have been applied on individuals. 111 individuals having colour vision deficiency and 137 individuals having normal colour vision have been participated to this thesis. In the name of just diagnosis if the individual is colour blind, the new test has achieved 100% specify and 100% sensitivity. With the final phase of the new test, it has been enabled to diagnosis of an individual in a detailed way and reveal the colour deficiency of each individual in terms of colour tones besides just classifying if the individual is colour blind. Furthermore, a fuzzy logic algorithm has been used to determine if the individuals has colour vision deficiency
- …