Color transformation for protanopia color vision deficiency using integration of image processing and artificial neural network

Color blindness deficiency is inability to distinguish colors with each other. Nowadays, the individual who are not being able to recognize color may be crucial in some day life situation because many common activities depend on signals with color-coded such as road sign, traffic light, electric wir...

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Main Author:	Abd. Wahab, Nur Hidayatul Nadihah
Format:	Thesis
Language:	English
Published:	2015
Subjects:	TK Electrical engineering Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/id/eprint/78871/1/NurhidayatulNadihahAbdMFKE2015.pdf
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spelling	my-utm-ep.788712018-09-17T07:15:47Z Color transformation for protanopia color vision deficiency using integration of image processing and artificial neural network 2015-12 Abd. Wahab, Nur Hidayatul Nadihah TK Electrical engineering. Electronics Nuclear engineering Color blindness deficiency is inability to distinguish colors with each other. Nowadays, the individual who are not being able to recognize color may be crucial in some day life situation because many common activities depend on signals with color-coded such as road sign, traffic light, electric wire, resistor and many more. There are many forms of color blindness such Monochromacy (total color blindness), Dichromacy (Red/ Green/Blue blindness) and Trichromacy and etc. Most types of defective color blindness can be classified into two categories which are green color defective and red color defective. The objective of this project is to improve the ability of color discrimination for Protanopia which a type of dichromacy where the patients does not naturally develop red color or Long wavelength cones in their eyes. This project proposed a method using image processing to improve the ability of color discrimination for Protanopia as well as adjusting images such that a person suffering from Protanopia is able perceive image detail and color dynamics. This method is first developed by simulating an image through the eyes of a person suffering from protanopia by converting RGB space to LMS (long, medium, short) color space based on cone response and then modifies the response of the deficient cones. The linear multiplication matrix is derived by referring to CIE color matching functions. ANN is then set up by using the input/output from matrix conversion. For this research, the ANN is introduced to reduce simulation time in image processing. The transformation technique used is RGB Color Contrasting where this step is to enhance contrast between red and green which in general, make green pixels appear to be bluer. Based on the result, the objectives are successfully achieved. ANN gives the minimum computational time than conventional matrix conversion which is 36% increment. The changes of the image drastically for both color blind and non-color blind viewers. The result shows that the reds become redder and greens become greener from the image before being adjusted. 2015-12 Thesis http://eprints.utm.my/id/eprint/78871/ http://eprints.utm.my/id/eprint/78871/1/NurhidayatulNadihahAbdMFKE2015.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:106107 masters Universiti Teknologi Malaysia, Faculty of Electrical Engineering Faculty of Electrical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TK Electrical engineering Electronics Nuclear engineering
spellingShingle	TK Electrical engineering Electronics Nuclear engineering Abd. Wahab, Nur Hidayatul Nadihah Color transformation for protanopia color vision deficiency using integration of image processing and artificial neural network
description	Color blindness deficiency is inability to distinguish colors with each other. Nowadays, the individual who are not being able to recognize color may be crucial in some day life situation because many common activities depend on signals with color-coded such as road sign, traffic light, electric wire, resistor and many more. There are many forms of color blindness such Monochromacy (total color blindness), Dichromacy (Red/ Green/Blue blindness) and Trichromacy and etc. Most types of defective color blindness can be classified into two categories which are green color defective and red color defective. The objective of this project is to improve the ability of color discrimination for Protanopia which a type of dichromacy where the patients does not naturally develop red color or Long wavelength cones in their eyes. This project proposed a method using image processing to improve the ability of color discrimination for Protanopia as well as adjusting images such that a person suffering from Protanopia is able perceive image detail and color dynamics. This method is first developed by simulating an image through the eyes of a person suffering from protanopia by converting RGB space to LMS (long, medium, short) color space based on cone response and then modifies the response of the deficient cones. The linear multiplication matrix is derived by referring to CIE color matching functions. ANN is then set up by using the input/output from matrix conversion. For this research, the ANN is introduced to reduce simulation time in image processing. The transformation technique used is RGB Color Contrasting where this step is to enhance contrast between red and green which in general, make green pixels appear to be bluer. Based on the result, the objectives are successfully achieved. ANN gives the minimum computational time than conventional matrix conversion which is 36% increment. The changes of the image drastically for both color blind and non-color blind viewers. The result shows that the reds become redder and greens become greener from the image before being adjusted.
format	Thesis
qualification_level	Master's degree
author	Abd. Wahab, Nur Hidayatul Nadihah
author_facet	Abd. Wahab, Nur Hidayatul Nadihah
author_sort	Abd. Wahab, Nur Hidayatul Nadihah
title	Color transformation for protanopia color vision deficiency using integration of image processing and artificial neural network
title_short	Color transformation for protanopia color vision deficiency using integration of image processing and artificial neural network
title_full	Color transformation for protanopia color vision deficiency using integration of image processing and artificial neural network
title_fullStr	Color transformation for protanopia color vision deficiency using integration of image processing and artificial neural network
title_full_unstemmed	Color transformation for protanopia color vision deficiency using integration of image processing and artificial neural network
title_sort	color transformation for protanopia color vision deficiency using integration of image processing and artificial neural network
granting_institution	Universiti Teknologi Malaysia, Faculty of Electrical Engineering
granting_department	Faculty of Electrical Engineering
publishDate	2015
url	http://eprints.utm.my/id/eprint/78871/1/NurhidayatulNadihahAbdMFKE2015.pdf
_version_	1747818091860983808

Color transformation for protanopia color vision deficiency using integration of image processing and artificial neural network

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