4.4 Article

Improved colour-to-grey method using image segmentation and colour difference model for colour vision deficiency

期刊

IET IMAGE PROCESSING
卷 12, 期 3, 页码 314-319

出版社

INST ENGINEERING TECHNOLOGY-IET
DOI: 10.1049/iet-ipr.2017.0482

关键词

image segmentation; image colour analysis; computer vision; image segmentation; colour difference model; colour vision deficiency; CVD; improved colour-to-grey method; genetic condition; colour image; region growing method; arbitrary segmented region pairs; greyscale image; E-score

资金

  1. China Postdoctoral Science Foundation [2016M592763]
  2. Fundamental Research Funds for the Central Universities [JB161001, JB161006]
  3. Shaanxi Science and Technology Research Projects [D14013230107]
  4. National Natural Science Foundation of China [61401324, 61305109]

向作者/读者索取更多资源

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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