Perceptual correction for colour grading using sensor transformations and metameric data

Abstract. We present a method of colour shade grading for industrial inspection of surfaces, the differences of which are at the threshold of human perception. This method converts the input data from the electronic sensor to the corresponding data as they would have been viewed using the human vision system. Then their differences are computed using a perceptually uniform colour space, thus approximating the way the human experts would grade the product. The transformation from the electronic sensor to the human sensor makes use of synthetic metameric data to determine the transformation parameters. The method has been tested using real data.

[1]  Keinosuke Fukunaga,et al.  Introduction to Statistical Pattern Recognition , 1972 .

[2]  J. Mollon,et al.  Human visual pigments: microspectrophotometric results from the eyes of seven persons , 1983, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[3]  Josef Kittler,et al.  An integrated system for quality inspection of tiles , 1997 .

[4]  Audrey Tarrant,et al.  Color in Business, Science and Industry , 1976 .

[5]  Y. Nayatani,et al.  New Method for Generating Metameric Stimuli of Object Colors , 1972 .

[6]  Josef Kittler,et al.  Automatic grading of textured ceramic tiles , 1995, Electronic Imaging.

[7]  Majid Mirmehdi,et al.  Ceramic tile inspection for colour and structural defects , 1995 .

[8]  Günter Wyszecki,et al.  Evaluation of Metameric Colors , 1958 .

[9]  P L Walraven,et al.  A closer look at the tritanopic convergence point. , 1974, Vision research.

[10]  J. Pokorny,et al.  Full-spectrum cone sensitivity functions for X-chromosome-linked anomalous trichromats. , 1992, Journal of the Optical Society of America. A, Optics and image science.

[11]  Josef Kittler,et al.  Automatic color grading of ceramic tiles using machine vision , 1997, IEEE Trans. Ind. Electron..

[12]  Kobus Barnard,et al.  COMPUTATIONAL COLOR CONSTANCY: TAKING THEORY INTO PRACTICE , 1995 .

[13]  J. J. Vos Colorimetric and photometric properties of a 2° fundamental observer , 1978 .

[14]  Josef Kittler,et al.  Automatic grading of ceramic tiles using machine vision , 1994, Proceedings of 1994 IEEE International Symposium on Industrial Electronics (ISIE'94).

[15]  J. Pokorny,et al.  Spectral sensitivity of the foveal cone photopigments between 400 and 500 nm , 1975, Vision Research.

[16]  W. A. Thornton Toward a more accurate and extensible colorimetry. Part I. Introduction. the visual colorimeter‐spectroradiometer. Experimental results , 1992 .

[17]  W. Stiles,et al.  N.P.L. Colour-matching Investigation: Final Report (1958) , 1959 .

[18]  J. J. Vos,et al.  On the derivation of the foveal receptor primaries. , 1971, Vision research.

[19]  W. Stiles,et al.  Interim Report to the Commission Internationale de l'Eclairage, Zurich, 1955, on the National Physical Laboratory's Investigation of Colour-matching (1955) , 1955 .

[20]  J. Guild The Colorimetric Properties of the Spectrum , 1932 .

[21]  Majid Mirmehdi,et al.  Automatic inspection of ceramic tiles , 1994 .

[22]  Keinosuke Fukunaga,et al.  Introduction to statistical pattern recognition (2nd ed.) , 1990 .

[23]  W. D. Wright A re-determination of the trichromatic coefficients of the spectral colours , 1929 .