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 language | English |
|---|---|
| Pages (from-to) | 314 – 319 |
| Number of pages | 6 |
| Journal | IET Image Processing |
| Volume | 12 |
| Issue number | 3 |
| Early online date | 23 Nov 2017 |
| DOIs | |
| Publication status | Published - 1 Mar 2018 |
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Zhang, L., Xu, Q., Zhu, G., Song, J., Zhang, X., Shen, P., Wei, W., Shah, S. A., & Bennamoun, M. (2018). An Improved Colour-to-Grey Method Using Image Segmentation and the Colour Difference Model for Colour Vision Deficiency. IET Image Processing, 12(3), 314 – 319. https://doi.org/10.1049/iet-ipr.2017.0482