ix congreso nacional del color

IX CONGRESO NACIONAL DEL COLOR ALICANTE 2010

SEDOPTICA

S O C I E D A D E S PA Ñ O L A D E Ó P T I C A

COMITÉ

E S PA Ñ O L

DE

COLOR

PUBLICACIONES UNIVERSIDAD DE ALICANTE

www.sri.ua.es/congresos/color10

Alicante, 29 y 30 de Junio, 1 y 2 de Julio de 2010 Universidad de Alicante

Este libro ha sido debidamente examinado y valorado por evaluadores ajenos a la Universidad de Alicante, con el in de garantizar la calidad cientíica del mismo.

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© Varios autores, 2010 © de la presente edición: Universidad de Alicante

ISBN: 978-84-9717-144-1

Diseño de portada: candelaInk

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IX CONGRESO NACIONAL DEL COLOR. ALICANTE 2010

El IX Congreso Nacional de Color cuenta con el apoyo de las siguientes entidades:

IX CNC -Libro de Actas-


IX Congreso Nacional de Color Alicante, 29 y 30 de Junio, 1 y 2 de Julio Universidad de Alicante

Departamento de Óptica, Farmacología y Anatomía Facultad de Ciencias Instituto Universitario de Física Aplicada a las Ciencias y las Tecnologías (IUFACyT) Universidad de Alicante



COMITÉ ORGANIZADOR Presidente Vicepresidente I

Francisco M. Martínez Verdú Universidad de Alicante Eduardo Gilabert Pérez

Universidad Politécnica de Valencia

Vicepresidente II

Joaquín Campos Acosta

IFA-CSIC

Secretaria Científica

Esther Perales Romero

Universidad de Alicante

Secretaria Administrativa

Olimpia Mas Martínez


Secretaria Técnica

Sabrina Dal Pont


Tesorero

Valentín Viqueira Pérez


Vocal

Elísabet Chorro Calderón


Vocal

Verónica Marchante


Vocal

Bárbara Micó Vicent


Vocal

Elena Marchante


Vocal

Ernesto R. Baena Murillo


COMITÉ CIENTÍFICO Natividad Alcón Gargallo

Instituto de Óptica, Color e Imagen, AIDO

Joaquín Campos Acosta

Instituto de Física Aplicada CSIC

Pascual Capilla Perea

Universidad de Valencia

Ángela García Codoner


Eduardo Gilabert Pérez


José Mª González Cuasante

Universidad Complutense de Madrid

Francisco José Heredia Mira

Universidad de Sevilla

Enrique Hita Villaverde

Universidad de Granada

Luís Jiménez del Barco Jaldo


Julio Antonio Lillo Jover

Universidad Complutense de Madrid

Francisco M. Martínez Verdú


Manuel Melgosa Latorre


Ángel Ignacio Negueruela

Universidad de Zaragoza

Susana Otero Belmar

Instituto de Óptica, Color e Imagen, AIDO

Jaume Pujol Ramo

Universidad Politécnica de Cataluña

Javier Romero Mora


Mª Isabel Suero López

Universidad de Extremadura

Meritxell Vilaseca Ricart

Universidad Politécnica de Cataluña



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) Martina Grosman1,

, Luis Gómez8Robledo2, Manuel Melgosa2, Samuel Morillas3, Ana Carrasco2 1 Dept. of Textiles, Faculty of Natural Sciences and Engineering, University of Ljubljana, Ljubljana (Slovenia). 2 Dept. of Optics, University of Granada, Granada (Spain). 3 Instituto Universitario de Matemática Pura y Aplicada, Universidad Politécnica de Valencia, Valencia (Spain). http://www.ugr.es/~basapplcolor/, [email protected]

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! > Obtaining color coordinates from an image is a complicated process, in which calibration and characterization of the camera are essential. However, it is interesting to study what can be obtained if the camera is not calibrated. This work achieves an approximation to this study. Two different commercial cameras have been employed to obtain images of 8 different color samples. No calibration of the cameras has been performed, recovering CIELAB coordinates of the samples through Adobe Photoshop software. The results have been compared with the CIELAB coordinates computed from the spectral radiance of the samples measured with a spectroradiometer. The illumination was controlled putting the samples in a GretagMacbeth boothlight provided with a daylight simulator lamp. In this work the aperture of the cameras was fixed in 5.6. Nevertheless the sensitivity (ISO values) and exposure time have been systematically changed. The results show differences between the cameras, the samples and the setup of sensitivity and exposure time. The average color differences of the samples are 10.83 and 18.79 CIELAB units for the two cameras with the optimal combinations of ISO value and exposure time. ; ?@

> Color Measurement, Digital Camera, ISO Value, Exposure Time, CIELAB. 9

Color imaging is becoming more important in the measurement of color, displacing in some applications to spectroradiometers, spectrophotometers or colorimeters. Different techniques are used to recover tristimulus values from the color data saved in an image [1, 2]. All of them require the calibration and characterization of the camera used to capture the image. In this work we study if it is possible to obtain colorimetric information from a non8calibrated commercial camera, and the accuracy of the obtained data. Undeniably, calibration of the camera is necessary, and this work does not claim to avoid it [3]. Nevertheless, this work analyzes how far the non8 calibrated measurements from the correct values are.

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The samples employed to collect colorimetric data were selected from a printed sheet with 33x49 colors, taken from the magazine Test Targets 6.0, page 64, published by School of Print Media, Rochester Institute of Technology in 2006, as it is shown in Fig. 1. From it, 8 basic color samples were selected, as is shown in Fig. 2. These colors are Red (31x49), Green (32x49), Blue (33x49), Cyan (28x49), Magenta (29x49), Yellow (30x49), Black (33+1x49) and White (33+1x48). The numbers in brackets are the color coordinates in the printed sheet. Alternatively it 259


would be used a standardized color chart as the GretagMacbeth ColorChecker Color Rendition (CCCR) or the GretagMacbeth ColorChecker SG (CCSG).

Figure 1. Printed sheet with 33x49 color samples.

Figure 2. Squares with the same color as the patches employed for color measurements.

Two commercial digital photographic cameras were employed in the work, a Canon EOS 350d and a Nikon D80. The Canon camera has resolution of 8 megapixels, CMOS optical sensor with size 22.2x14.8 mm and the Nikon has resolution of 10.2 megapixels and CCD optical sensor with size 23.6x15.8 mm. On Canon camera was used a 28880 mm objective, with maximum aperture f/3.5 at 28 mm, and f/5.6 at 80 mm. On Nikon camera was used a Nikkor 188135 mm objective, with maximum aperture f/3.5 at 18 mm, and f/5.6 at 135 mm. For both cameras, the aperture was set on the medium value 5.6 and it was not changed throughout the images acquisition process. However, different ISO values, from 100 to 1600, and exposure times, between 1/15 and 1/250 s, were employed. The photographs were saved in JPG format with a resolution of 3456x2304 (8 megapixels). The Adobe Photoshop CS3 software was used to obtain colorimetric data, CIELAB coordinates, from the photos, selecting an area of a single pixel, approximately in the center of the chip image. Bearing in mind that in case of non8calibrated cameras the transformation used in the Adobe Photoshop software is no completely appropriated because this transformation is really device dependent; the CIELAB coordinates obtained from the images acquired with each camera have been compared with the ones computes from spectroradiometric measurements, performed with a spectroradiometer PhotoReseach SpectraScan PR8704, using a aperture of 0.125º. As perfect diffuser, a surface of PTFE11, supplied with the spectroradiometer, were used. The CIE 1931 Standard Observer has been considered in the computation of triestimulus values. Table 1 shows the CIELAB color coordinates of the 8 used samples computed from the spectroradiometric measurements.

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PTFE corresponds to polytetrafluoroethylene, which is an organic polymer.

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Table 1. CIELAB color coordinates of the samples.

L* a* b* C*ab hab

Red 59.66 41.83 25.00 48.73 30.87

Green 63.52 -39.67 23.14 45.92 149.74

Blue 43.83 19.30 -20.86 28.42 312.78

Cyan 67.18 -28.63 -34.36 44.73 230.20

Magenta 59.70 53.39 6.22 53.75 6.64

Yellow 89.31 -3.68 63.27 63.37 93.33

Black 24.72 2.24 3.19 3.90 54.91

White 99.22 -0.04 0.06

Both, digital photographs and spectroradiometric measurements, were performed in a GretagMacbeth Spectralight III cabinet provide with a light8source that simulates very well the illuminant D65 [4], putting the sheet in the center of the boothlight.

)93 ) Obviously not all the possible combinations of ISO values and exposure time are appropriated, because some combinations results in over or supra exposition of the image. Fig. 3 illustrates this statement in the case of the cyan color.

Figure 3. Images (camera Canon EOS 350d) for color cyan with different ISO values and exposure.

The optimal exposure of the photograph can be achieved with different combinations of ISO value and exposure time, as can be seen in Fig. 3. These combinations correspond to the diagonal of Fig. 3. In these optimal exposure images, the CIELAB coordinates have been obtained through the Photoshop software. Table 2 shows the color difference in CIELAB unit between each image and the CIELAB coordinates computed from the spectroradiometric measurements. Grey background denotes the lowest values for each color and camera. Table 2. CIELAB color differences, ∆E*ab, for optimal expositions. Color

Canon

Nikon

ISO 100 200 400 800 1600 100 200 400 800 1600

Exposure time 1/15 1/30 1/60 1/125 1/250 1/15 1/30 1/60 1/125 1/250

Red

Green

Blue

Cyan

Magenta

Yellow

Black

White

7.18 7.56 7.45 9.32 7.80 17.79 19.39 17.84 17.99 19.17

12.10 10.19 10.82 9.34 13.40 24.61 25.05 23.20 23.20 23.30

10.58 11.82 12.46 12.36 14.54 9.24 12.33 9.72 9.31 7.40

7.85 9.92 8.97 10.10 9.53 12.62 10.19 15.61 18.26 17.44

10.63 10.84 12.35 12.94 14.48 17.06 17.22 19.18 19.78 19.34

4.84 5.41 5.56 6.20 7.97 19.27 19.68 23.35 20.55 22.26

35.45 36.54 39.55 40.43 38.48 52.66 55.22 43.79 42.16 52.27

0.79 3.52 3.52 2.29 3.18 15.12 13.29 15.69 17.20 16.52

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Table 1 shows very different color differences for each color patch. The darker colors are usually the furthest from the spectroradiometric measure. On the other hand, white and light colors have the lower color differences. Also there are important differences between the CIELAB coordinates recover from each camera, obtaining the Canon the lowest values in almost all cases. The best combination ISO value and exposure time is different for each camera and color, but most of the cases correspond to ISO 100 and exposure time 1/15 s. The lowest color differences corresponding to the optimal combinations are marked with grey background. Considering the optimal setup of sensitivity and exposure time, the average color differences of the samples are 10.83 and 18.79 CIELAB units for the Canon and Nikon cameras respectively. Similar standard deviation is achieved for the Canon (10.47 CIELAB units) versus Nikon (10.72 CIELAB units).

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To recover properly colorimetric data from an image, calibration of the camera is unavoidable. Fixing the aperture, the optimal setup for sensitivity and exposure time depend of the camera and the color. Considering the best results, important color differences are obtained in all cases, varying from 0.76 to 42.16 CIELAB units. The results also show a clear dependency with the camera. Applying the transformation included in the Adobe Photoshop software Canon obtain better results. This transformation, which is standard and no consider calibration, cause a bias of the results, more important for the Nikon camera.

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This research had been supported by the Egide agency (France) via the Partenariat Hubert Curien Franco8Espagnol (Program Picasso Nº 19258SF) and by the Ministerio de Ciencia e Innovación (Spain) via the Acción Integrada España8Francia (Program HF200880056). Also Research Project FIS2007864266, Ministerio de Educación y Ciencia (Spain), with ERDF (European Regional Development Fund) support.

) [1] F. H. Imai, R. S. Berns, "Spectral Estimation Using Trichromatic Digital Cameras", Proceedings of the 1st European Conference of Colour in Graphics, Image and Vision, 492896 (1999). [2] E. M. Valero, J. L. Nieves, S. M. C. Nascimento, K. Amano,K., D. H. Foster, "Recovering spectral scenes with an RGB and colored filters data from natural digital camera", Color Research and Application 32, 352860 (2007). [3] Healey, G. E. and R. Kondepudy, "Radiometric CCD Camera Calibration and Noise Estimation", IEEE Transactions on Pattern Analysis and Machine Intelligence 16, 267876 (1994). [4] R. Roa, R. Huertas, M.A. López8Álvarez, L. Gómez8Robledo, M. Melgosa, “Comparación entre iluminantes y Fuentes simuladoras”, Óptica Pura y Aplicada 41, 2918300 (2008).

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