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    ISO TR 16066-2003 Graphic technology - Standard object colour spectra database for colour reproduction evaluation (SOCS)《图形技术 彩色再现评估(SOCS)用标准物体颜色波谱数据库》.pdf

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    ISO TR 16066-2003 Graphic technology - Standard object colour spectra database for colour reproduction evaluation (SOCS)《图形技术 彩色再现评估(SOCS)用标准物体颜色波谱数据库》.pdf

    1、 Access to Additional Content for ISO/TR 16066 First Edition, Dated: 03/15/2003 (Click here to view the publication) This Page is not part of the original publication This page has been added by IHS as a convenience to the user in order to provide access to additional content as authorized by the Co

    2、pyright holder of this document Click the link(s) below to access the content and use normal procedures for downloading or opening the files. ISO TR 16066 Extra Files Information contained in the above is the property of the Copyright holder and all Notice of Disclaimer the PDF-creation parameters w

    3、ere optimized for printing. Every care has been taken to ensure that the file is suitable for use by ISO member bodies. In the unlikely event that a problem relating to it is found, please inform the Central Secretariat at the address given below. ISO 2003 All rights reserved. Unless otherwise speci

    4、fied, no part of this publication may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying and microfilm, without permission in writing from either ISO at the address below or ISOs member body in the country of the requester. ISO copyright office Ca

    5、se postale 56 CH-1211 Geneva 20 Tel. + 41 22 749 01 11 Fax + 41 22 749 09 47 E-mail copyrightiso.org Web www.iso.org Published in Switzerland ii ISO 2003 All rights reservedISO/TR 16066:2003(E) ISO 2003 All rights reserved iiiContents Page Foreword iv Introduction v 1 Scope 1 2 Standard object colou

    6、r spectra . 1 2.1 Object categories and sample selection 1 2.2 Typical set samples and difference set samples. 4 3 Use of the colour spectra database 5 3.1 Use of typical sets. 5 3.2 Use of difference sets. 7 4 Permissions. 8 Annex A (informative) Spectral reflectance and transmittance source data 9

    7、 Annex B (normative) Typical set selection method for artificial colour groups 27 Annex C (normative) Typical set selection method for non-skin colour, natural colour groups 29 Annex D (normative) Typical set selection method for skin groups. 31 Annex E (normative) Difference set selection method. 3

    8、2 Annex F (informative) Correspondence between typical/difference samples and original collected data samples . 33 ISO/TR 16066:2003(E) iv ISO 2003 All rights reservedForeword ISO (the International Organization for Standardization) is a worldwide federation of national standards bodies (ISO member

    9、bodies). The work of preparing International Standards is normally carried out through ISO technical committees. Each member body interested in a subject for which a technical committee has been established has the right to be represented on that committee. International organizations, governmental

    10、and non-governmental, in liaison with ISO, also take part in the work. ISO collaborates closely with the International Electrotechnical Commission (IEC) on all matters of electrotechnical standardization. International Standards are drafted in accordance with the rules given in the ISO/IEC Directive

    11、s, Part 2. The main task of technical committees is to prepare International Standards. Draft International Standards adopted by the technical committees are circulated to the member bodies for voting. Publication as an International Standard requires approval by at least 75 % of the member bodies c

    12、asting a vote. In exceptional circumstances, when a technical committee has collected data of a different kind from that which is normally published as an International Standard (“state of the art”, for example), it may decide by a simple majority vote of its participating members to publish a Techn

    13、ical Report. A Technical Report is entirely informative in nature and does not have to be reviewed until the data it provides are considered to be no longer valid or useful. Attention is drawn to the possibility that some of the elements of this document may be the subject of patent rights. ISO shal

    14、l not be held responsible for identifying any or all such patent rights. ISO/TR 16066 was prepared by Technical Committee ISO/TC 130, Graphic technology. The TC 130 Japanese National Committee prepared this database, and their efforts have made this Technical Report possible. The original form of th

    15、is report was published as a technical report TR X 0012 by the Japanese Standards Association in Japanese in December 1998. ISO/TR 16066:2003(E) ISO 2003 All rights reserved vIntroduction The simplest way to evaluate the colour reproduction of colour image input devices is to input images of objects

    16、 whose colours are exactly known and then to compare the pixel values to exact ones. For that purpose, input colour target standards have been already established in ISO 12641:1997, Graphic technology Prepress digital data exchange Colour targets for input scanner calibration. Evaluation becomes mor

    17、e complicated, however, when we consider metamers. The perceived colours of a pair of objects are referred to as metamers if, under a particular illumination, they have the same tristimulus values even though they are spectrally different. The spectral pairs of such objects may be used to advantage

    18、in the assessment of differences among lighting conditions. If, for instance, a pair of spectra yield the same tristimulus values X, Y, Z under CIE illuminant D50, the difference between the two perceived colours of the pair of spectra as measured in the field under a different illumination is refer

    19、red to as a metameric index, which can be used as a measure of the non-conformance of that illumination to D50. While it may be sometimes preferable, e.g. for standards purposes, to use artificial pairs of perceived colours, i.e. those not coming from natural objects, natural metameric pairs have th

    20、e advantage that one can assess the effect of non-standard lighting for a particular lighting condition. One may find, for instance, that a particular light source leads to unacceptably large deviations in skin tones, whereas the same source is quite acceptable for furniture colours. Definitions wit

    21、h respect to metameric indices and the procedures for their evaluation are described in the following CIE publications: CIE 15.2, Colorimetry, 2nd ed. (1986) (Contains Special Metamerism Index: Change in Illuminant) CIE 51.2, A method for assessing the quality of daylight simulators for colorimetry

    22、(1999) CIE 80, Special metamerism index: Change in observer (1989) It can also be useful to consider metamers in the evaluation of such colour image input devices as colour scanners and digital cameras, which, though designed to capture images in a way similar to that of the human visual system (HVS

    23、), nonetheless deviate enough from HVS sensitivity so that colour reproduction of sensed colours in display devices or print outputs are significantly different from that desired, even when the illumination conditions of the original human observation of an object have been recreated for the observa

    24、tion of the output image. To evaluate deviations due to variations in light sources and/or sensor sensitivities under actual conditions, it is useful to know the range of spectral differences in existing objects. Committee members have created an exhaustive collection of colours of existing objects,

    25、 a database containing more than 50 000 items. This report details the extraction from the data of 365 colour samples and their classification into sets, of which there are two types, “typical sets” and “difference sets”. “Typical sets” refers to sets of typical spectral reflectances and transmittan

    26、ces of objects as classified into a number of different categories. “Difference sets” refers to sets of metamers whose tristimulus values are roughly typical but whose spectral values are significantly non-typical. The entire original collection of more than 50 000 spectral data items is included, i

    27、n electronic form, as part of this Technical Report in the data directory SourceData as described in Annex A. TECHNICAL REPORT ISO/TR 16066:2003(E) ISO 2003 All rights reserved 1Graphic technology Standard object colour spectra database for colour reproduction evaluation (SOCS) 1 Scope This Technica

    28、l Report provides a database of typical and difference sets of existing object colour spectral data that are suitable for evaluating the colour reproduction of image input devices. It also includes the spectral reflectance and transmittance source data from which these data sets have been derived. 2

    29、 Standard object colour spectra 2.1 Object categories and sample selection 2.1.1 Categories and groups The following categories and subcategories were first established: (1) Photographic materials a. Transparencies b. Reflection prints (2) Offset prints (3) Computer colour prints a. Dye sublimation

    30、printer b. Electrostatic printer c. Ink-jet printer (4) Paint (not for art) (5) Paints (for art) a. Oil paints b. Water colours (6) Textiles a. Synthetic dyes b. Plant dyes (7) Flowers and leaves (8) Outdoor scenes (Krinov data except for flowers and leaves) ISO/TR 16066:2003(E) 2 ISO 2003 All right

    31、s reserved(9) Human skin a. Bare North Asian skin b. Foundation-applied North Asian skin c. Bare South Asian skin d. Foundation-applied South Asian skin e. Bare Caucasian skin f. Bare Negroid skin Spectral reflectance/transmittance data were then collected for more than 50 000 items falling into the

    32、se categories/subcategories. Categories (1) to (5) and subcategory (6)a are for artificial colours, while subcategory (6)b and categories (7) to (9) are for natural colours. Typical sets and difference sets were established from 365 samples in this database. A typical set is a set of representative

    33、spectral data of colour objects, while a difference set is a set of metamers whose colour under D65 illuminant is similar to typical set samples but differs significantly from them spectrally. Samples for the typical and difference sets were selected as shown in Table 1. The manner of selecting typi

    34、cal samples depended on whether colours were artificial or natural. In most artificial colour groups, all colours are synthesized by mixing three or four colorants, and distributed almost uniformly in their colour gamut. Colours in the paint (not for art) and paints (for art) categories, however, ar

    35、e synthesized by mixing more than four colorants, and these categories were dealt with in the same manner as with natural colours. Selection strategies are described in following subsections. Table 1 Numbers of selected typical/difference set colour samples Group Typical sets Difference sets Photo (

    36、transparency) 15 15 Photo (reflection print) 15 15 Offset prints 15 15 Dye sublimation printer 15 15 Electrostatic printer 15 15 Ink-jet printer 15 15 Textiles (synthetic dyes) 15 15 Flowers/grasses/leaves (includes Krinovs grasses and leaves) 25 25 Paint (not for art) 15 Oil paints 15 Water colours

    37、 15 Textiles (plant) 15 Non-grass/leaf Krinov 15 Bare North Asian skin 5 FD-applied North Asian skin 5 Bare South Asian skin 5 FD-applied South Asian skin 5 Bare Caucasian skin 5 Bare Negroid skin 5 Total 365 ISO/TR 16066:2003(E) ISO 2003 All rights reserved 3NOTE Foundation is a cosmetic used as a

    38、base for facial make-up. However, in this Technical Report, foundation applied skin means skin that is not bare, but covered with foundation and/or face powder. 2.1.2 Typical set selection for artificial colour groups There are seven artificial colour groups in Table 1: photographic transparency, ph

    39、otographic reflection prints, offset prints, dye sublimation printer, electrostatic printer, ink-jet printer, and textiles (synthetic dyes). Colour samples can be obtained for every hue in these groups. Colorants can be expected to vary within any one group, as, for example, among the many products

    40、of different photographic prints material manufacturers. Spectral reflectance measurements were carried out for several representative products among them. Statistical analysis was carried out on the measurement data, and the product whose characteristics most closely approximated the statistical av

    41、erage for the products as a whole was determined to be a typical colour product. A mathematical explanation for this is found in Annex B. From a large number of colour samples for a typical product, fifteen samples were selected whose colours are nearest to pre-determined basic colours, which consis

    42、t of three achromatic colours and twelve chromatic colours that are homogeneously distributed in twelve hues. Lightness and chromaticity of each chromatic colour was such that the colour gamut of each artificial colour group contained all the chromatic colours. Table 2 shows the achromatic colours (

    43、1-3) and the chromatic colours (4-15). The colour for each spectral data is calculated under D65 illuminant. Table 2 Basic colours for artificial colour groups L* H* C* a* b* 1 20 0 0,0 0,0 2 50 0 0,0 0,0 3 80 0 0,0 0,0 4 40 0 30 30,0 0,0 5 45 30 35 30,3 17,5 6 50 60 37 18,5 32,0 7 60 90 45 0,0 45,0

    44、 8 60 120 30 15,0 26,0 9 45 150 30 26,0 15,0 10 45 180 23 23,0 0,0 11 45 210 22 19,1 11,0 12 45 240 20 10,0 17,3 13 40 270 20 0,0 20,0 14 35 300 27 13,5 23,4 15 40 330 30 26,0 15,0 2.1.3 Typical set selection for non-skin colour, natural colour groups There are six natural colour groups in Table 1 f

    45、or non-skin colours: flowers/grasses/leaves (including Krinovs grasses/leaves), paint (not for art), oil paints, watercolours, textiles (plant), and non-grass/leaf Krinov. Samples in natural colour groups are not distributed in whole hues, and typical samples cannot be selected on the basis of their

    46、 colours. To select typical set samples for natural colour groups, an algorithm based on spectral distribution was developed. When principal component analysis was applied to all samples in a group, it became possible to express the data distribution in a low dimensional subspace. An equi-distanced

    47、lattice was set in the subspace, and a representative sample was selected from each lattice point. A mathematical explanation for this is found in Annex C. Twenty-five typical samples were selected from the flowers/grasses/leaves group, while 15 typical samples were selected from each of the other groups.


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