RGB Color Cluster and Graph Coloring Algorithm for Partial Color Blind Correction

Partial color blindness is an anomaly occurring to 5-8% of the world's population. Color correction using re-coloring algorithm usually can be used to help partial color blindness patient. One of the existing re-coloring techniques is to use the RGB color cluster technique and combine it by uti...

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Main Authors: Dody Qori Utama, Tati Latifah R. Mengko, Richard Mengko, Andika Prahasta Gandasubrata, Tauhid Nur Azhar
Format: Article
Language:English
Published: EDP Sciences 2019-01-01
Series:MATEC Web of Conferences
Online Access:https://doi.org/10.1051/matecconf/201925501002
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spelling doaj-8ec603e690d64feeb91bc578e04e86cd2021-02-02T06:59:34ZengEDP SciencesMATEC Web of Conferences2261-236X2019-01-012550100210.1051/matecconf/201925501002matecconf_eaaic2018_01002RGB Color Cluster and Graph Coloring Algorithm for Partial Color Blind CorrectionDody Qori Utama0Tati Latifah R. Mengko1Richard Mengko2Andika Prahasta Gandasubrata3Tauhid Nur Azhar4Biomedical Engineering Department, School of Electrical Engineering and Informatics, Institut Teknologi BandungBiomedical Engineering Department, School of Electrical Engineering and Informatics, Institut Teknologi BandungBiomedical Engineering Department, School of Electrical Engineering and Informatics, Institut Teknologi BandungFaculty of Medicine, Universitas Padjajaran and Rumah Sakit Mata CicendoFaculty of Medicine, Universitas Islam BandungPartial color blindness is an anomaly occurring to 5-8% of the world's population. Color correction using re-coloring algorithm usually can be used to help partial color blindness patient. One of the existing re-coloring techniques is to use the RGB color cluster technique and combine it by utilizing the brute force algorithm to perform color tracing for correcting the color. It has massive time and memory complexity. This research aims to create a correction technique for color blind people using RGB Color Cluster combined with Graph Coloring Algorithm. The first process is to get the RGB color cluster for color blind subject. After getting RGB color cluster from the subject then the image which want to be corrected is grouped based on RGB color cluster. The threshold of color grouping in image is done by utilizing the upper and lower bound values of the RGB color cluster. After the cluster is grouped, then we can represent neighbourhood between the colors by utilizing graph. The adjacent color group will be a neighbour. The next process is color re-coloring using graph coloring algorithm. In graph coloring algorithm, same color group is prohibited to become neighbour. In this research, graph coloring algorithm is used to prevent 2 colors that are look almost similar for become neighbours because it will cause the subject cannot distinguish it. Re-coloring is done by increasing and decreasing the color intensity of a set of colors. This technique succeeds in decreasing the complexity of the brute force algorithm from O(N4) to O(2N2) where the first N2 is the complexity of building the cluster group and the second N2 is the complexity of the re- coloring. In addition, the color of the object becomes more natural because Re-coloring is based on color group not pixel based.https://doi.org/10.1051/matecconf/201925501002
collection DOAJ
language English
format Article
sources DOAJ
author Dody Qori Utama
Tati Latifah R. Mengko
Richard Mengko
Andika Prahasta Gandasubrata
Tauhid Nur Azhar
spellingShingle Dody Qori Utama
Tati Latifah R. Mengko
Richard Mengko
Andika Prahasta Gandasubrata
Tauhid Nur Azhar
RGB Color Cluster and Graph Coloring Algorithm for Partial Color Blind Correction
MATEC Web of Conferences
author_facet Dody Qori Utama
Tati Latifah R. Mengko
Richard Mengko
Andika Prahasta Gandasubrata
Tauhid Nur Azhar
author_sort Dody Qori Utama
title RGB Color Cluster and Graph Coloring Algorithm for Partial Color Blind Correction
title_short RGB Color Cluster and Graph Coloring Algorithm for Partial Color Blind Correction
title_full RGB Color Cluster and Graph Coloring Algorithm for Partial Color Blind Correction
title_fullStr RGB Color Cluster and Graph Coloring Algorithm for Partial Color Blind Correction
title_full_unstemmed RGB Color Cluster and Graph Coloring Algorithm for Partial Color Blind Correction
title_sort rgb color cluster and graph coloring algorithm for partial color blind correction
publisher EDP Sciences
series MATEC Web of Conferences
issn 2261-236X
publishDate 2019-01-01
description Partial color blindness is an anomaly occurring to 5-8% of the world's population. Color correction using re-coloring algorithm usually can be used to help partial color blindness patient. One of the existing re-coloring techniques is to use the RGB color cluster technique and combine it by utilizing the brute force algorithm to perform color tracing for correcting the color. It has massive time and memory complexity. This research aims to create a correction technique for color blind people using RGB Color Cluster combined with Graph Coloring Algorithm. The first process is to get the RGB color cluster for color blind subject. After getting RGB color cluster from the subject then the image which want to be corrected is grouped based on RGB color cluster. The threshold of color grouping in image is done by utilizing the upper and lower bound values of the RGB color cluster. After the cluster is grouped, then we can represent neighbourhood between the colors by utilizing graph. The adjacent color group will be a neighbour. The next process is color re-coloring using graph coloring algorithm. In graph coloring algorithm, same color group is prohibited to become neighbour. In this research, graph coloring algorithm is used to prevent 2 colors that are look almost similar for become neighbours because it will cause the subject cannot distinguish it. Re-coloring is done by increasing and decreasing the color intensity of a set of colors. This technique succeeds in decreasing the complexity of the brute force algorithm from O(N4) to O(2N2) where the first N2 is the complexity of building the cluster group and the second N2 is the complexity of the re- coloring. In addition, the color of the object becomes more natural because Re-coloring is based on color group not pixel based.
url https://doi.org/10.1051/matecconf/201925501002
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AT richardmengko rgbcolorclusterandgraphcoloringalgorithmforpartialcolorblindcorrection
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AT tauhidnurazhar rgbcolorclusterandgraphcoloringalgorithmforpartialcolorblindcorrection
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