An Improved Colour-to-Grey Method Using Image Segmentation and the Colour Difference Model for Colour Vision Deficiency

Liang Zhang, Qing Xu, Guangming Zhu, Juan Song, Xiangdong Zhang, Peiyi Shen, Wei Wei, Syed Afaq Shah, Mohammed Bennamoun

Research output: Contribution to journal › Article

1 Citation (Scopus)

Abstract

Colour vision deficiency (CVD) is a genetic condition that has troubled people for a long time. This study proposes an improved colour-to-grey method for CVD using image segmentation and a colour difference model. In this method, the colour image is first segmented using a region growing method so that each region corresponds to one colour. Next, the colour difference is computed between arbitrary segmented region pairs. Finally, the greyscale image is obtained by minimising a target function. Experimental results show that compared with state-of-the-art colour-to-grey methods, the proposed algorithm can improve the E-score by about 10.99%.
Original languageEnglish
Pages (from-to)314 – 319
Number of pages6
JournalIET Image Processing
Volume12
Issue number3
Early online date23 Nov 2017
DOIs
Publication statusPublished - 1 Mar 2018

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Color vision
Image segmentation
Color

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Zhang, Liang ; Xu, Qing ; Zhu, Guangming ; Song, Juan ; Zhang, Xiangdong ; Shen, Peiyi ; Wei, Wei ; Shah, Syed Afaq ; Bennamoun, Mohammed. / An Improved Colour-to-Grey Method Using Image Segmentation and the Colour Difference Model for Colour Vision Deficiency. In: IET Image Processing. 2018 ; Vol. 12, No. 3. pp. 314 – 319.
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abstract = "Colour vision deficiency (CVD) is a genetic condition that has troubled people for a long time. This study proposes an improved colour-to-grey method for CVD using image segmentation and a colour difference model. In this method, the colour image is first segmented using a region growing method so that each region corresponds to one colour. Next, the colour difference is computed between arbitrary segmented region pairs. Finally, the greyscale image is obtained by minimising a target function. Experimental results show that compared with state-of-the-art colour-to-grey methods, the proposed algorithm can improve the E-score by about 10.99{\%}.",
author = "Liang Zhang and Qing Xu and Guangming Zhu and Juan Song and Xiangdong Zhang and Peiyi Shen and Wei Wei and Shah, {Syed Afaq} and Mohammed Bennamoun",
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Zhang, L, Xu, Q, Zhu, G, Song, J, Zhang, X, Shen, P, Wei, W, Shah, SA & Bennamoun, M 2018, 'An Improved Colour-to-Grey Method Using Image Segmentation and the Colour Difference Model for Colour Vision Deficiency' IET Image Processing, vol. 12, no. 3, pp. 314 – 319. https://doi.org/10.1049/iet-ipr.2017.0482

An Improved Colour-to-Grey Method Using Image Segmentation and the Colour Difference Model for Colour Vision Deficiency. / Zhang, Liang; Xu, Qing ; Zhu, Guangming; Song, Juan; Zhang, Xiangdong ; Shen, Peiyi; Wei, Wei; Shah, Syed Afaq; Bennamoun, Mohammed.

In: IET Image Processing, Vol. 12, No. 3, 01.03.2018, p. 314 – 319.

Research output: Contribution to journal › Article

TY - JOUR

T1 - An Improved Colour-to-Grey Method Using Image Segmentation and the Colour Difference Model for Colour Vision Deficiency

AU - Zhang, Liang

AU - Xu, Qing

AU - Zhu, Guangming

AU - Song, Juan

AU - Zhang, Xiangdong

AU - Shen, Peiyi

AU - Wei, Wei

AU - Shah, Syed Afaq

AU - Bennamoun, Mohammed

PY - 2018/3/1

Y1 - 2018/3/1

N2 - Colour vision deficiency (CVD) is a genetic condition that has troubled people for a long time. This study proposes an improved colour-to-grey method for CVD using image segmentation and a colour difference model. In this method, the colour image is first segmented using a region growing method so that each region corresponds to one colour. Next, the colour difference is computed between arbitrary segmented region pairs. Finally, the greyscale image is obtained by minimising a target function. Experimental results show that compared with state-of-the-art colour-to-grey methods, the proposed algorithm can improve the E-score by about 10.99%.

AB - Colour vision deficiency (CVD) is a genetic condition that has troubled people for a long time. This study proposes an improved colour-to-grey method for CVD using image segmentation and a colour difference model. In this method, the colour image is first segmented using a region growing method so that each region corresponds to one colour. Next, the colour difference is computed between arbitrary segmented region pairs. Finally, the greyscale image is obtained by minimising a target function. Experimental results show that compared with state-of-the-art colour-to-grey methods, the proposed algorithm can improve the E-score by about 10.99%.

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Zhang L, Xu Q, Zhu G, Song J, Zhang X, Shen P et al. An Improved Colour-to-Grey Method Using Image Segmentation and the Colour Difference Model for Colour Vision Deficiency. IET Image Processing. 2018 Mar 1;12(3):314 – 319. https://doi.org/10.1049/iet-ipr.2017.0482

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