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Improving Information Perception from Digital Images for Users with Dichromatic Color Vision Omid Shayeghpour

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Improving Information Perception from Digital Images for Users with Dichromatic Color Vision Omid Shayeghpour LiU-ITN-TEK-A--13/047--SE Improving information perception from digital images for users with dichromatic color vision Omid Shayeghpour 2013-09-23 Department of Science and Technology Institutionen för teknik och naturvetenskap Linköping University Linköpings universitet nedewS ,gnipökrroN 47 106-ES 47 ,gnipökrroN nedewS 106 47 gnipökrroN LiU-ITN-TEK-A--13/047--SE Improving information perception from digital images for users with dichromatic color vision Examensarbete utfört i Medieteknik vid Tekniska högskolan vid Linköpings universitet Omid Shayeghpour Handledare Sasan Gooran Examinator Daniel Nyström Norrköping 2013-09-23 Upphovsrätt Detta dokument hålls tillgängligt på Internet – eller dess framtida ersättare – under en längre tid från publiceringsdatum under förutsättning att inga extra- ordinära omständigheter uppstår. 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För ytterligare information om Linköping University Electronic Press se förlagets hemsida http://www.ep.liu.se/ Copyright The publishers will keep this document online on the Internet - or its possible replacement - for a considerable time from the date of publication barring exceptional circumstances. The online availability of the document implies a permanent permission for anyone to read, to download, to print out single copies for your own use and to use it unchanged for any non-commercial research and educational purpose. Subsequent transfers of copyright cannot revoke this permission. All other uses of the document are conditional on the consent of the copyright owner. The publisher has taken technical and administrative measures to assure authenticity, security and accessibility. According to intellectual property law the author has the right to be mentioned when his/her work is accessed as described above and to be protected against infringement. For additional information about the Linköping University Electronic Press and its procedures for publication and for assurance of document integrity, please refer to its WWW home page: http://www.ep.liu.se/ © Omid Shayeghpour Color vision deficiency (CVD) is the inability or limited ability to recognize colors and discriminate between them. A person with this condition perceives a narrower range of colors compared to a person with a normal color vision. A growing number of researchers are striving to improve the quality of life for CVD patients. Finding cure, making rectification equipment, providing simulation tools and applying color transformation methods are among the efforts being made by researchers in this field. In this study we concentrate on recoloring digital images in such a way that users with CVD, especially dichromats, perceive more details from the recolored images compared to the original image. The main focus is to give the CVD user a chance to find information within the picture which they could not perceive before. However, this transformed image might look strange or unnatural to users with normal color vision. During this color transformation process, the goal is to keep the overall contrast of the image constant while adjusting the colors that might cause confusion for the CVD user. First, each pixel in the RGB-image is converted to HSV color space in order to be able to control hue, saturation and intensity for each pixel and then safe and problematic hue ranges need to be found. The method for recognizing these ranges was inspired by a condition called “unilateral dichromacy” in which the patient has normal color vision in one eye and dichromacy in another. A special grid-like color card is designed, having constant saturation and intensity over the entire image, while the hue smoothly changes from one block to another to cover the entire hue range. The next step is to simulate the way this color card is perceived by a dichromatic user and finally to find the colors that are perceived identically from two images and the ones that differ too much. This part makes our method highly customizable and we can apply it to other types of CVD, even personalize it for the color vision of a specific observer. The resulting problematic colors need to be dealt with by shifting the hue or saturation based on some pre-defined rules. The results for the method have been evaluated both objectively and subjectively. First, we simulated a set of images as they would be perceived by a dichromat and compared them with simulated view of our transformed images. The results clearly show that our recolored images can eliminate a lot of confusion from user and convey more details. Moreover, an online questionnaire was created and 39 users with CVD confirmed that the transformed images allow them to perceive more information compared to the original images. 1 Color vision deficient users have problem discriminating different colors. In chapter 1, we will introduce CVD and discuss its causes and types and how to diagnose such conditions. The project objectives as well as our goals for this thesis will be presented in this chapter as well. Chapter 2 will be dedicated to the basic information about digital color imaging. This chapter begins with the introduction to the different color spaces that will be required in the rest of this thesis and concludes by explaining how a typical simulation tool, simulates the vision of a color vision deficient user. In Chapter 3, our main method will be explained in details. First, a brief background of different efforts done in the field of CVD will be presented. Throughout the rest of this chapter we will explain in detail our goals and how we try to achieve them in this thesis. Various test images will be utilized in this chapter which somewhat cover some part of our results as well. In Chapter 4, we will discuss a few other distinct approaches that other researchers introduced in order to tackle problems of similar manner. We will also try to show some parts of their result sets to generate an understanding about possible differences between these approaches and our proposed method. We have tested our method in two ways: first, we compared the dichromatic simulation of the original image with the simulation of our transformed image and evaluated if our method improved the information perception or not. This type of evaluation was done throughout Chapters 3 and 4 while the basics of how such a simulation takes place was presented in Chapter 2. Second, we tried to validate our work by testing the results through actual color vision deficient patients. Several pictures were transformed by our method and through a questionnaire we asked different questions about those pictures before and after transformation. Those results will be presented in Chapter 5. We will present a suggestion for the future work in this field by combining our method with the personalized simulation that will also be explained in Chapter 5. A short summary of our work will conclude this chapter. 2 .......................................................................................................................................................... 1 ................................................................................................................................................... 2 Introduction to Color Vision Deficiencies ................................................................................................. 5 1.1Cause .................................................................................................................................................... 5 1.2 Types ................................................................................................................................................... 6 1.2.1 Total color blindness .................................................................................................................... 6 1.2.2 Partial color blindness ................................................................................................................. 7 1.2.2.1 Protanopia ............................................................................................................................ 7 1.2.2.2 Deuteranopia ........................................................................................................................ 8 1.2.2.3 Tritanopia ............................................................................................................................. 9 1.3 Diagnosis.......................................................................................................................................... 10 1.4 Research objective .......................................................................................................................... 11 Digital Color Imaging & Simulation tools .............................................................................................
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