DETERMINATION OF THE EFFECT OF GRAY COMPONENT REPLACEMENT LEVEL ON COLORIMETRIC CHARACTERISTICS OF COLOR PROOF

Journal of Chemical Technology I. Spiridonov, and M. Metallurgy, Shopova 48, 3, 2013, 247-253 DETERMINATION OF THE EFFECT OF GRAY COMPONENT REPLACEMENT LEVEL ON COLORIMETRIC CHARACTERISTICS OF COLOR PROOF I. Spiridonov, M. Shopova University of Chemical Technology and Metallurgy 8 Kl. Ohridski, 1756 Sofia, Bulgaria E-mail: i_spiridonov@abv.bg Received 20 December 2012 Accepted 15 May 2013 ABSTRACT The main goal of this study is determination the effect of GCR (gray component replacement) levels on colorimetric characteristics of color proof. To determine the effect of GCR levels on colors of color proofs, a comparison of 2D and 3D color gamuts depending on GCR level have been performed. In addition to obtain better assessment of the effect of GCR levels on color gamut were calculate volumes of 3D color gamuts and 2D surface areas. In order to determine the effect of GCR on colorimetric characteristics is performed colorimetric evaluation, expressed as color difference ΔE * ab. Keywords: gray component replacement, color gamut, color proof. INTRODUCTION The main purpose of using a digital color proofing press is to simulate the visual characteristics of the finished production prints as closely as possible. In our study the aim is to simulate four color sheet-fed offset press with specification FOGRA39. In conventional multicolor printing, the chromatic inks cyan (C), magenta (M) and yellow (Y) reproduce the color shades, and black ink is used to increase image quality and save inks. Increasing of image quality is expressed as increasing the gamut size, improving the details, obtaining more dark colors and making gray balance more stable [1-3]. An important characteristic of an output device is its color gamut, or the range of its reproducible colors. This range of colors can be thought of as a volume in 3D color space. The gamut is usually specified in a colorimetric or visually based space such as CIE L*a*b*, where L* correspond to lightness, a* to red-green color (+a* - red, -a* - green), and b* to yellow-blue color (+b* - yellow, -b* - blue). Knowledge of the size and shape of color gamut surface is useful for determination how colors outside the color gamut should be reproduced [4-7]. There are several methods for generation and controlling the amount of substitution of chromatic colors cyan, magenta and yellow (CMY) with black ink. The most commonly implemented method in practice for generation of achromatic composition is GCR (gray component replacement). Many CMY combinations contain certain amount of gray component. The gray component is a combination of inks which, if printed alone, will produce a neutral gray. The replacement of gray component with black ink reduce the total amount of ink without changes in colors [8, 9]. Theoretically the substitution of chromatic inks with a black one can be easily performed, but in practice there are certain inaccuracies, especially in neutral colors. For more than 50% reduction of chromatic inks (50% GCR), differences occur. Using the higher level of reduction of the chromatic inks lead to lowest optical density and lightness in shadow tones. Improper settings of GCR level can cause significant color deviations in the image, because black ink cannot replace the colorfulness 247

Journal of Chemical Technology and Metallurgy, 48, 3, 2013 of chromatic inks [10, 11]. The main goal of this study is determination the effect of GCR (gray component replacement) levels on colorimetric characteristics of color proof. To determine the effect of GCR levels on colors of color proofs, a comparison of 2D and 3D color gamuts depending on GCR level have been performed. In addition to obtain better assessment of the effect of GCR levels on color gamut were calculate volumes of 3D color gamuts and 2D surface areas. In order to determine the effect of GCR on colorimetric characteristics is performed colorimetric evaluation, expressed as color difference ΔE*ab. The color difference was calculated after conversion of spectral data to CIE L*a*b* color coordinates. EXPERIMENTAL A special test form that contain different control strips and elements, test chart ECI 2002 CMYK random, test images has been designed. The test chart ECI 2002 CMYK random contains 1485 color patches with different combinations of cyan, magenta, yellow and black, which are used to evaluate the effect of GCR level. The test form was printed on Proofing System Epson Stylus Pro 9900, color proofing device, certified for color conformation of offset lithography printing ISO 12647-2 [12, 13]. The used paper and inks are in accordance to ISO 12647-7 [14]. In order to visually match a specific printing condition, proofing processes requires a set of parameters to be specified that are not necessarily identical to those listed in ISO 12647-1 or another part of ISO 12647. This is caused by differences in colorant spectra or phenomena such as gloss, light scatter (within the print substrate or the colorant), and transparency. Therefore a spectrophotometer/ densitometer SpectroEye of X-Rite has been used for measuring a color characteristics in the CIE L*a*b* color space. All measurements are in accordance with ISO standards: D50 illuminant, 2 observer, 0/45 or 45/0 geometry, black backing. The spectral measurements shows, that the digital color proofing system is simulating correctly the colors according to ISO 12647-7. A spectral measurements have been performed for the printed test charts using spectrophotometer X-Rite i1pro and automatic scanning device i1i0, considering 248 values in the wavelength range of 380 to 730 nm with a step of 10 nm (internal step 5 nm). The measurements are performed according to ISO 13656 [15]. Four ICC color profiles have been created by Profile Maker, X-Rite, with GCR minimum level (signed below as min GCR), with medium GCR (signed below as GCR 1), with heavy GCR (signed below as GCR 2) and with maximum GCR (signed below as max GCR). Each of these four ICC profiles was applied to the test form and was printed under the same print conditions. The visualization of color gamuts and calculation of color gamut volumes were performed with Color Think Pro, Chromix and Surfer, Golden Software Inc. A series of spectral measurements (at the conditions listed above) with different GCR levels have been made for each printing sheet. The spectral data were converted to tristimulus values CIE XYZ. [16, 17] CIE L*a*b* values were calculated from the tristimulus values. The color difference ΔE*ab was calculated (the calculations for ΔE*ab were performed to GCR minimal value as a reference). RESULTS AND DISCUSSION 3D and 2D presentation of color gamuts gives precise and comprehensive information of colors, that can be reproduced in the specific conditions. Presentation of 3D color gamut provides general information and shows the shape of color body. 2D gamut presentation at different cross-section of CIE L* coordinate, gives more detailed information for analyses and comparison. Therefore it is very important to determine changes in color gamuts in dependence of gray component replacement level. At Fig. 1 are presented 3D color gamuts depending on GCR level viewed from different angles. The comparison of 3D color gamuts (Fig. 1) shows that GCR maximal level has generally the biggest color gamut. It is clearly visible that using minimal level of GCR lead to lower color gamut. 2D gamuts at different cross-section of CIE L* coordinate for dark, middle and highlight tones are presented on Fig. 2. These cross-sections of 3D hull of color gamut are chosen, because the human eye has a different sensitivity in dark, middle and highlight tones. Fig. 2 shows that in the dark tones (Fig. 2 a and 2b) the color gamut at minimal level of GCR is consider-

I. Spiridonov, M. Shopova Fig. 1. Comparison of 3D color gamuts for different GCR levels in CIE L * a * b *. ably smaller than the others. The biggest color gamut is obtained at maximal level of GCR. The color gamuts at maximal level of GCR and level 2 of GCR are similar. In yellow-green area at L= 22 (figure 2a) the color gamuts are similar, except color gamut at minimal level of GCR, and in blue-violet area at L = 30 (Fig. 2b) all color gamuts are similar. In middle tones (Fig. 2c) generally all color gamuts are similar, but only in one small part in yellow area difference occur. In highlight tones (Fig. 2d and 2e) the biggest color gamut is obtained at level 2 of GCR, and the smallest color gamut, at maximal level of GCR. In yellow-green and yellow-red areas the color gamuts are similar. In addition to graphical comparison of color gamuts we have calculated color gamut volumes. The obtained results are given in Table 1. According to the results shown in Table 1, the biggest color gamut volume is obtained at maximal level of GCR and the smallest at minimal level of GCR. The highest difference in volumes of color gamuts is only 2%, and the lowest 0.58%. A difference in color gamut volumes with such magnitude is negligible. GCR maximal level has generally the biggest color gamut and GCR minimal level has the smallest color gamut, which can be seen from 3D color gamuts (Fig. 1) and from their volumes (Table 1). For better assessment of changes in color gamuts the surface areas of 2D cross-sections of 3D color gamuts were calculated depending on GCR levels in highlights, middle and dark tones. Calculated surface areas are presented in Table 2. The obtained results shows that the values of surface areas at maximal level of GCR are considerable bigger than these for the others GCR levels. It is clearly visible that at CIE L* 17 to 60, the highest values of surface areas are obtained at maximal level of GCR, and the lowest values are obtained at minimal level of GCR. After that, CIE L* > 60, the highest values of surface areas are obtained at level 2 of GCR, and the lowest Table 1. Color gamut volumes depending on GCR levels. GCR level Color gamut volume, E 3 min 333966 1 338799 2 334590 max 340762 249

Journal of Chemical Technology and Metallurgy, 48, 3, 2013 Fig. 2. 2D color gamut of colors under different GCR levels in CIE L * a * b * : а/ by L * = 22 /dark tones/; b/ by L * = 30 /dark tones/; c/ by L * = 50 /middle tones/; d/ by L * = 75 /highlight tones/; e/ by L * =80 /highlight tones/. values - at maximal level of GCR. In order to determine the effect of GCR on colorimetric characteristics of color proof is performed colorimetric evaluation, expressed as color difference ΔE*ab. The color difference was calculated using GCR minimal level as a reference. The evaluation has been made for patches in highlights, middle and dark tones. Detailed information for these patches is represented in Table 3. These color patches have been chosen, because they represent some of most important tones and shades near the gray axis in CIE L*a*b* system. The obtained results for ΔE*ab in highlight tones are shown on figure 3, for ΔE*ab in middle tones on figure 4 and for ΔE*ab in dark tones on Fig. 5. The graph (Fig. 3) shows considerable small color difference, by human perception point of view. The minimal value of color difference is 0.12 units, and the maximal is 0.78 units, both obtained at GCR maximal level. It means that in tones and colors, which are close to neutral, the GCR level does not have a big impact for Table 2. Surface areas depending on GCR levels. At CIE L * Surface areas, E 2 GCR level min 1 2 max 17 56.45 121.96 202.28 254.48 22 207.77 547.57 542.16 827.94 25 724.96 1122.27 1450.23 1602.88 30 2133.55 2518.84 2829.92 3001.90 40 5191.19 5349.24 5469.56 5665.99 50 8010.02 8119.10 8124.80 8205.77 60 5219.62 5356.13 5474.69 5682.50 70 4595.20 4653.20 4705.93 4498.62 75 3439.24 3507.28 3603.24 3041.13 80 1982.88 2052.91 2383.85 1740.75 86 395.31 448.60 537.48 388.51 250

I. Spiridonov, M. Shopova Table 3. Tone value information for chromatic patches in highlight, middle and dark tones. Patch ID Cyan, % Magenta, % Yellow, % 2O32 3 3 3 2P32 5 3 3 W32 7 7 7 2R1 10 6 6 G17 10 10 10 A28 20 10 10 2S2 20 12 12 2G6 20 20 10 2S23 20 20 20 H26 30 20 20 2A16 40 30 30 M20 40 40 40 2L3 55 30 30 R20 55 40 40 F3 55 55 55 2U4 60 45 45 M19 70 40 40 E25 70 55 55 2G3 70 70 70 C32 85 55 55 A2 80 65 65 2H29 85 70 70 W31 100 85 85 O20 100 100 100 Highlight tones Middle tones Dark tones Fig. 3. ΔE * for printed colors in highlight tones depending ab on GCR level. Fig. 4. ΔE * for printed colors in middle tones depending ab on GCR level. color accuracy in tones near to gray axis. There is a big difference in values at patch 2L3 on Fig. 4. The highest value of ΔE*ab is 1.89 units (at maximal level of GCR) and the lowest value is 0.42 units. A difference with such magnitude is observed only for this patch. The graph on Fig. 5 shows that the highest values of color difference are obtained for solid patches. The lowest value of color difference is 0.41 units, and the highest 1.59 units. For more precise evaluation of the effect of GCR level color accuracy, it have been calculated the average color difference. The average color difference provide valuable information about differences in colors by human perception point of view. It is important because it shows the difference in all parts of spectral data, all shades and colors. The obtained results for average, minimal and maximal color difference for all 1485 patches are given in Table 4. The average color difference for all 1485 patches is Fig. 5. ΔE * for printed colors in dark tones depending on ab GCR level. calculated by equation 1. Field 1 Field 2 Field 1485 ESample/ GCR min + ESample/ GCR min +... + ESample/ GCR min EAVERAGE = 1485 (1) where, EAVERAGE mean arithmetic colour difference of 1485 measured fields between the specific GCR Field level sample and the GCR minimum level, ESample/ GCRmin 251

Journal of Chemical Technology and Metallurgy, 48, 3, 2013 Table 4. Average, maximal and minimal color difference. colour difference between a specific sample color field with different GCR level and the same field with minimum GCR level. According to the results listed in Table 4, the biggest average color difference is obtained for the GCR level 1. The smallest value of average color difference is obtained at GCR level 2. There is a small difference in values of average, minimal and maximal color difference (0.33 units E*ab, 0.04 units E*ab, and 0.53 units E*ab, respectively). It means that the difference remain relatively constant. CONCLUSIONS The comparison of 3D color gamuts shows that GCR maximal level has generally the biggest color gamut. It must be noted that using minimal level of GCR lead to lower color gamut. According to the results from comparison of 2D gamuts at cross-section of CIE L* coordinate in dark and middle tones the biggest color gamut is obtained at maximal level of GCR, and the smallest at minimal level of GCR. In highlight tones the biggest color gamut is obtained at level 2 of GCR, and the smallest color gamut, at maximal level of GCR. The results of calculated color gamut volumes shows that the biggest color gamut volume is obtained at maximal level of GCR and the smallest at minimal level of GCR. The highest difference in volumes of color gamuts is only 2 %, and the lowest 0.58 %. A difference in color gamut volumes with such magnitude is negligible. The obtained results for surface areas of 2D crosssections of 3D color gamuts shows that the values of surface areas at maximal level of GCR are considerable bigger than these for the others GCR levels. It is clearly visible that at CIE L* 17 to 60, the highest values of surface areas are obtained at maximal level 252 GCR level E * ab,average E * ab,min E * ab,max 1 0.93 0.03 5.54 2 0.60 0.06 5.17 max 0.77 0.02 5.70 of GCR, and the lowest values are obtained at minimal level of GCR. After that, CIE L* higher than 60 units, the highest values of surface areas are obtained at level 2 of GCR, and the lowest values - at maximal level of GCR. There is a big differences between surface areas up to 77 % at cross-sections in dark tones. This big difference decrease to 8 % at cross-sections in middle tones and to 27 % at cross-sections in highlight tones. This phenomenon is very important of practical point of view, because the volume of colors is one of the most important factors, that impact on human perception and therefore on print quality. Therefore it is very important to determine changes in color gamuts in dependence of gray component replacement level. GCR level 2 generally has color gamut similar to those at GCR maximal level in dark tones, meanwhile has the biggest color gamut in highlight tones. This is confirmed by the graphical comparison of color gamuts and by their volumes and surface areas. According to the results from colorimetric evaluation for colors in highlight tones, expressed as color difference ΔE*ab, there is considerable small color difference, by human perception point of view. The minimal value of color difference is 0.12 units, and the maximal is 0.78 units, both obtained at GCR maximal level. It means that in tones and colors, which are close to neutral, the GCR level does not have a big impact for color accuracy in tones near to gray axis. The color difference for printed colors in middle tones is about 1.89 units, and in dark tones 1.59 units. From human perception point of view that is considerable difference. For more precise evaluation of the effect of GCR level color accuracy, the average color difference have been calculated. According to the results, the biggest average color difference is obtained for the GCR level 1, and the smallest value is obtained at GCR level 2. There is a small difference in values of average, minimal and maximal color difference (0.33 units E*ab, 0.04 units E*ab, and 0.53 units E*ab, respectively). It means that the difference remain relatively constant. It must be noted that in dark tones GCR maximal level has the biggest color gamut, while in highlight tones, it has the smallest color gamut. The color gamuts at maximal level of GCR and level 2 of GCR are similar in dark tones, but in highlight tones GCR level 2 has the biggest color gamut. According to the colorimetric evaluation, GCR level 2 has the smallest maximal and

I. Spiridonov, M. Shopova average color difference. A research study and implementation of methodology from this research should be performed for running an experiment in conditions of sheetfed offset and web offset printing for different printing substrates. The results obtained from real production conditions should be compared with digital color proofs systems. In future, by collected data from this research, it could be developed mathematical model describing relationship between ink quantity of process colors - C, M, Y, K, GCR levels and color reproduction accuracy. Certainly it will be very useful for predicting of correct color reproduction and choosing the correct level of GCR in dependence of printing conditions. Acknowledgements This study was funded by the Bulgarian Science Fund (DMU 03/69/2011). REFERENCES 1. G. Sharma, Digital Color Imaging Handbook, CPC Press LLC, Boca Raton, FL, 2002. 2. H. Kipphan, Handbook of Print Media, Technologies and Production Methods, Springer-Verlag Heidelberg, Berlin, 2001. 3. B.-H. Kang, H.-K. Choh, C.-Y. Kim, Black color replacement using gamut extension method, NIP21: International Conference on Digital Printing Technologies, September 2005, 21, 384-386. 4. R. Balasubramanian, E. Dalal, A method for quantifying the color gamut of an output device, Proc. SPIE, 3018, 1997, 110 116. 5. T.J. Cholewo, S. Love, Gamut boundary determination using alpha-shapes, Proc. 7th Color Imaging Conference: Color Science, Systems and Applications, 7, 1999, 200 204. 6. I. Farup, J.Y. Hardeberg, A.M. Bakke, S. Kopperud, A Rindal, Visualization and interactive manipulation of color gamuts, Proc. IS&T and SID s, 10, 2002, 250 255. 7. I. Spiridonov, M. Shopova, R. Boeva, M.Nikolov, The effect of different standard illumination conditions on color balance failure in offset printed images on glossy coated paper expressed by color difference, Phys. Scr., T149, 2012, 014019. 8. E. Neumann, M. Bohan, Ink Optimization: An Evaluation of the Different Strategies, GATFWorld, 20, 2, 2008, 46-48. 9. R. de Queiroz, K. Braun, R. Loce, Detecting spatially varying gray component replacement with application in watermarking printed images, JEI-14-033016, 14, 3, 2005. 10. D. Agić, M. Gojo, M. Strgar-Kurečić, Determination of equivalent-density domain in black compensation implementation for selected profile, Technical Gazette, 18, 1, 2011, 63-68. 11.T. Costa, Effect of GCR and TAC in Color Gamut Volume, Test Targets 4.0, Advanced Color Management RIT School of Print Media, Rochester, New York, USA, 2004. 12. ISO 12647-2, Graphic technology - Process control for the production of half-tone colour separations, proof and production prints, Part 2: Offset lithographic processes, 2004. 13. ISO 12647-2/Amd.1, Graphic technology - Process control for the production of half-tone colour separations, proof and production prints, Part 2: Offset lithographic processes, 2007. 14. ISO 12647-7, Graphic technology - Process control for the production of half-tone colour separations, proof and production prints, Part 7: Proofing processes working directly from digital data, 2007. 15. ISO 13656, Graphic technology - Application of reflection densitometry and colorimetry to process control or evaluation of prints and proofs, 2000. 16. ISO 11664-1 (CIE S 014-1/E:2006), Colorimetry, Part 1: CIE standard colorimetric observers, 2007. 17. CIE 15, Technical Report Colorimetry, 3rd Edition, 2004. 253