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Methods for designing characterisation targets for digital cameras
Author(s) -
Chou YiFan,
Luo M Ronnier,
Li Changjun,
Cheung Vien,
Lee SanLiang
Publication year - 2013
Publication title -
coloration technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.297
H-Index - 49
eISSN - 1478-4408
pISSN - 1472-3581
DOI - 10.1111/cote.12022
Subject(s) - computer science , rgb color model , artificial intelligence , set (abstract data type) , computer vision , digital camera , ideal (ethics) , range (aeronautics) , polynomial , computer graphics (images) , mathematics , mathematical analysis , philosophy , materials science , epistemology , composite material , programming language
Characterisation targets usually include a set of physical coloured samples. A characterisation model can be derived between the colorimetric values (tristimulus values) and camera responses ( RGB values) taken from an imaging device such as a digital camera capturing the colours in the target. The performance of such a model is highly dependent upon the number of colours and the colour region in the characterisation target. An ideal characterisation target should provide accurate model prediction without requiring too many samples. In this paper, a computational method is presented for colour selections to train a camera characterisation model based on a fourth‐order polynomial model including 35 terms. Compared with other available methods, the newly developed method performed better. It is proposed that this method be applied to generate generic targets in terms of colorimetric values. These targets should work reasonably well for a wide range of materials.