Sci. Rep. Kanazawa Univ.
Vol.58, pp.1-12, 2014

Advanced Java-based application to process
thermoluminescence digital color images
Manabu OGATA1，＊, Noriko HASEBE2, Ayako INAGAKI1, Noritake ENDO3
1

Graduate School of Natural Science and Technology, Kanazawa University
Kakuma, Kanazawa, 920-1192, Japan

2

Institute of Natural and Environmental Technology, Kanazawa University
Kakuma, Kanazawa, 920-1192, Japan
3

College of Science and Engineering, Kanazawa University
Kakuma, Kanazawa, 920-1192, Japan* Corresponding author Email: oga835@gmail.com(Received January 11, 2015 and accepted in revised form February 7, 2015)

Abstract Dielectric minerals that interact with ionizing radiation emit
thermoluminescence when heated. The color of the emitted thermoluminescencevaries among different samples, even for the same minerals. TL color analysis can beused to study mineral provenance.
Thermoluminescence color images (TLCI) can be obtained using a digital camera.
Inagaki et al. (2010) created a Java application to handle RGB (red-green-blue)
information of each pixel. This Java application is able to visually represent
thermoluminescence color on a CIE (Commission Internationale de l’Eclairage)
chromaticity diagram. Here, we report an improved Java application that enables thenumerical treatment of TLCI of various image sizes and resolutions. This application
allows for the handling of many digital TLCI in a short time and it is useful forstatistical color analyses.
Keywords: thermoluminescence, thermoluminescence color image, mineralprovenance

1 Introduction
When dielectric minerals interact with ionizing radiation, semi-stable electron and hole-12Advanced Java-based application to process thermoluminescence digital color images

trapping sites are created within the forbidden band. These minerals emit luminescencewhen heated and this phenomenon is referred to as thermoluminescence (TL). Quartz,
feldspar and calcite are known to be TL emitters in the geoscience field. The emitted
luminescence intensity is proportional to the accumulated dose given to the mineral byenvironmental radioisotopes. Therefore, TL can be applied to the dating ofarchaeological artifacts, volcanic products and sediments (Liritzis et al., 1996; Ganzawa
and Ike, 2011; Franklin et al., 1988).
The color of the emitted luminescence varies among samples, even among those of
the same minerals. Quartz emits blue or red thermoluminescence depending on its origin(Hashimoto et al., 1986a). TL color analysis can be used to study the provenance ofminerals. Hashimoto et al. (1986b) suggested a convenient method to observe
thermoluminescence color images (TLCI) of quartz using a commercial camera.
Ganzawa and Kubokita (2001) identified a widespread aeolian deposit and tephra byinvestigating the TL color characteristics on a Munsell color system color chart or a CIE
chromaticity diagram that was established by the Commission Internationale del’Eclairage (CIE). By taking a luminescence photo with a camera, the TL color of eachgrain can be observed and the TL color can be determined numerically and digitized.
Inagaki et al. (2010) obtained TLCI with a digital camera based on previous work
(Hashimoto et al., 1989; Ganzawa and Kubokita, 2001). Earlier studies only evaluateddigital TLCI qualitatively by plotting chromaticity diagrams. However, Inagaki et al.
(2010) developed a Java application to manipulate RGB information from TLCI. Theirsoftware enables the convenient, rapid and statistical analysis of TLCI. Hasebe et al.
(2012) applied this program to a core sample recovered from the lake bed sediment.
Sequential TLCI numerical information was compared with other analytical data andwas discussed as a proxy for environmental changes.
The Java application reported by Inagaki et al. (2010) is restricted to 800×800 pixel
image data and its flexibility is thus limited. However, image size may depend on
instrumental conditions (e.g. camera and sample heater), camera settings when theimage is captured, and the sample size. Therefore, we improved the Java application andapplied it to images of different sizes and resolutions to extend the scope of TLCI
analyses.

2 Digitization of TLCI
2.1

Numerical conversion

Thermoluminescence digital color images were obtained by the method proposed by
Inagaki et al. (2010) and then handled quantitatively and numerically in the CIE color

M. Ogata, N. Hasebe, A. Inagaki, N. Endo3system (Ganzawa and Kubokita, 2001; Fig. 1). The RGB information of each pixel wasread in the 0-255 range. To match with visible light, the RGB values were converted to
X, Y and Z by the following formula as determined by CIE:
X = 2.7689R+1.7517G+1.1302B
Y=
R+4.5907G+0.0601B
Z=
0.0565G+5.5943B
X, Y and Z were then converted to plane coordinate values, x and y.
x = X/(X+Y+Z)
y = Y/(X+Y+Z)
These x and y values were plotted on a CIE chromaticity diagram (Fig. 1). On the CIE
chromaticity diagram, the colors are represented continuously along the locus: blue,
green, yellow, orange and red from short wavelength to long wavelength. Based on
previous studies (Hashimoto et al., 1989; Ganzawa and Kubokita, 2001), five colorzones are defined and they are blue (B; B≦495 nm), green (G; 495 < G≦565 nm),yellow (Y; 565 < Y≦580 nm), and red (R; 580 nm < R). The fifth color zone is GAP,
which is the area formed by connecting the saturated purple line with the standard whiteline (Fig. 1). Each pixel color is categorized into one of these five color zones.

Fig. 1 CIE (Commission Internationale del’Eclairage) chromaticity diagram and thefive color zones defined in this study. B:
blue (-495 nm); G: green (495-565 nm); Y:
yellow (565-580 nm); R: red (580 nm-);gap: other.

2.2

Application

Inagaki et al. (2010) created a Java application to handle the thermoluminescence digitalcolor image numerically. Java was developed by Sun Microsystems Inc. and is platform-independent. The RGB information of one pixel is read by a method (function)
implemented in Java. The application developed by Inagaki et al. (2010) calculated the4Advanced Java-based application to process thermoluminescence digital color images

color information of each pixel (x and y) and the number of pixels in each color zone
(blue, green, yellow, red and GAP), and output was as a text file. To visualize the color
characteristics, the pixel information is plotted on a CIE chronometry diagram. Whenseveral pixels are plotted on the same coordinate, the number of pixels is represented byshading each plotted symbol (darker indicates more). In the application by Inagaki et al.
(2010), the point color plotted on the CIE chromaticity diagram is subject to the numberof counts. For example, if the number of pixels per coordinate is >100, the color of theplot is black. For >50 it is gray and so on. Therefore, the Java-based application written
by Inagaki et al. (2010) can only be applied to TLCI of particular size and/or resolution(applicable to TLCI of 800×800 pixels). If the image size is significantly more than
640,000, the plotted points are always black or vice versa.
We thus report an improved Java-based application for TLCI to evaluate the color
characteristics of images of various sizes and resolutions. In this application, the plotted
point color depends on the ratio of the number of counts/the number of measured pixels.
The pixels are divided into five levels (black, dark gray, gray, light gray and white), andthe threshold value for each level (class) can be set by the user. If the ratio of thenumber of counts/the number of measured pixels is less than the lowest threshold value,
no pixel information is plotted although the data is included in the generated text file.
Additionally, “the number of measured pixels” (denominator) can be selected as either ablack pixels (BP) included-type or a BP excluded-type. For the “BP included-type”, allimage pixels are used and for the “BP excluded-type” all pixels apart from the black
pixels (R+G+B < 30) are used. The BP included-type plot may be useful when theamount of luminous minerals is discussed, while the BP excluded-type plot may be
useful to obtain information of color combinations on luminous minerals. This Javaapplication can be used for all image sizes and resolutions.
Additionally, the number of pixels in each color zone (blue, green, yellow, red andgaps) can be counted and output as a text file by our Java application as was the case forthe application by Inagaki et al. (2010).
This new application can be downloaded for free from the website of the author’slaboratory (http://earth.s.kanazawa-u.ac.jp/chronology/).

2.3

Software usage

To evaluate the use of this new Java application to TLCI of various file sizes and TL
colors, we investigated the TLCI of quartz, calcite and feldspar with various resolutions(Fig. 2). The thermoluminescence colors of quartz, calcite and feldspar are blue, red andmultiple colors, respectively. The TLCI sizes were 1365×1365 (quartz; Fig. 2(a)), 544×583 (calcite; Fig. 2(b)) and 695×695 (feldspar; Fig. 2 (c)) pixels.
Figure 3 shows the results of the TLCI analysis by the Java application with the BP

M. Ogata, N. Hasebe, A. Inagaki, N. Endo

5

Fig. 2 TLCI of (a) quartz (low resolution: 251×
251 pixels), (b) calcite (544×583 pixels), (c)feldspar (695×695 pixels) and (d) quartz (highresolution: 1365×1365). (a) and (d) quartz
aliquots from the same sample.

Table 1

The number of counted color pixels in each color zone obtained from the TLCI analysis.

SampleRed

Yellow

Green

Blue

GAP

Black

Total

Quartz

103

410

635

113369064728323

1863225

Calcite184986

0

0

24

6

132136317152

Feldspar

15537

903

4191

27672

1107

433615483025*Red: 580 nm-, Yellow: 565-580 nm, Green: 495-565 nm, Blue: -495 nm, GAP: other zone, and Black: R+G+B < 30.

included-type. The class boundary values used to set the plot (symbol) colors were 0.1,
0.01, 0.005, 0.001 and 0.0001%. The number of pixels in each color zone could be6Advanced Java-based application to process thermoluminescence digital color images

Fig. 3 Results of TLCI analysis using ourJava application with the BP included-type.
The class boundary values used to set the plot
colors that represent the number of pixels were0.1, 0.01, 0.005, 0.001 and 0.0001%. The
analyzed TLCIs are from (a) quartz (Fig. 2(a)),(b) calcite (Fig. 2(b)), (c) feldspar (Fig. 2(c))
and (d) quartz (Fig. 2(d)). Circles show the
proportion of each color. Each color comesfrom the corresponding color zone.

counted and output was as a text file from our Java application (Table 1). Pie charts
were drawn using the obtained information and they are shown in Fig. 3 together with achronometry diagrams. The TLCI information for quartz, with blue TL as shown in Fig.
2(a), was plotted within the blue zone on the CIE chromaticity diagram (Fig. 3(a)).
However, the pixels in the TLCI of calcite, with red TL as shown in Fig. 2(b), wasplotted within the red zone on the CIE chromaticity diagram (Fig. 3(b)). For feldspar
that emitted various colors, the plotted points are widely dispersed over the CIE
chromaticity diagram (Fig. 3(c)).
To evaluate the flexibility of this Java application to TLCI of various file sizes,
mixture of quartz, which emits blue thermoluminescence (Fig. 2(a)), and calcite, whichemits red thermoluminescence (Fig. 2(b)), was prepared and TLCI was investigated (Fig.

M. Ogata, N. Hasebe, A. Inagaki, N. Endo

7

Fig. 4 Results of TLCI analysis with BP excluded type for the mixture sample (quartz and calcite) andfeldspar. The class boundary values used to set the plot colors were 1, 0.1, 0.05, 0.01 and 0.001%. For
mixture sample, file size is (a) 1846×1845, (b) 695×695 and (c) 200×200. For feldspar, (d) 695×695 and(e) 200×200. Circles show the proportion of each color. Each color comes from the corresponding color
zone.

8

Advanced Java-based application to process thermoluminescence digital color images

Table 2 The number of counted color pixels in each color zone obtained from the TLCI analyses of
mixture sample and feldspar.
Sample1846×1845
Mixture695×695
200×200

Red (R)
828602117704
9744

Yellow
1272
182
26

Green
4572
673
113

Blue (B)
1197512170021
14180

GAP
45986
6761
599

Black
1327926
187684
15338

Total
340587048302540000

R/B ratio
0.69
0.69
0.69

695×695
200×200

15537
1725

903
115

4191
391

27672
3366

1107
496

43361533907

483025
40000

0.56
0.51

Feldspar*R/B ratio was the ratio of the number of red pixels over the number of blue pixels.

4(a)). The original TLCI was 1846×1845 pixels in size. Then resolution was artificiallydecreased to 695×695 (Fig. 4(b)) and 200×200 (Fig. 4(c)) pixels. The original TLCI of
feldspar (Fig. 4(d), the same photo with Fig. 2(c)) was also investigated by artificiallydecreasing the resolution of TLCI to 200×200 pixels (Fig. 4(e)). The results of TLCI
analysis by the Java application with the BP excluded type were also shown in Fig. 4.
The class boundary values used to set the plot colors were 1, 0.1, 0.05, 0.01 and 0.001%.
The number of pixels in each color zone was shown in Table 2. Pie charts to show
numerical information are included in Fig. 4 together with a chronometry diagrams.
For the mixture sample, all TLCIs resulted in similar plots on the CIE chromaticity
diagram. TLCI of this sample was dominated by red or blue thermoluminescence (Table2). The number of red and blue pixels decreased from TLCI of high resolution (1846×
1845) to that of low resolution (200×200). However, the ratios in the number of red
pixels over the number of blue pixels (R/B ratio) were almost the same with all
resolutions, thus, the color combinations were almost identical for all TLCIs of the
mixture sample with difference file size. For feldspar, however, TLCI with highresolution (Fig. 4(d)) resulted in a plot with wider distribution than that with low
resolution (Fig. 4(e)). R/B ratio of TLCI with high resolution was higher than that withlow resolution. Additionally, the ratio in the number of green against total colored pixels
of TLCI was higher in high resolution than in low resolution (Pie charts of Fig. 4(d) and(e)). These differences between two resolutions may be caused by pixels which form theboundary of colored area.
A threshold in resolution of TLCI for a stable result depends on pattern of color
distribution in an observed area, which may vary sample to sample depending on
luminescence intensity and/or particle size of measured sample. At least the resolution
over 200×200 pixels will be necessary to analyze sample with discrete color distribution,
as is found in our feldspar image.
The Java application reported here is thus able to reproduce the thermoluminescencecolor from the TLCI on the CIE chromaticity diagram regardless of image size. It is able
to distinguish thermoluminescence color. Although the sizes of these TLCI are different,
this work shows that this Java application can be applied to all images. This indicatesthe flexibility of this Java application.

M. Ogata, N. Hasebe, A. Inagaki, N. Endo

9

Fig. 5 Results for TLCI analysis withdifferent sets of class boundary values using
the BP included-type. They are: (a) 0.1, 0.01,
0.005, 0.001 and 0.0001%; (b) 0.5, 0.05,
0.025, 0.005 and 0.0005%; (c) 1, 0.1, 0.05,
0.01 and 0.001%. Analyzed TLCI is fromfeldspar (Fig. 2 (c)).

Different sets of class boundary values were evaluated by TLCI of feldspar analyses(Fig. 5). They were: (a) 0.1, 0.01, 0.005, 0.001 and 0.0001; (b) 0.5, 0.05, 0.025, 0.005
and 0.0005; (c) 1, 0.1, 0.05, 0.01 and 0.001. The threshold values increased from pattern(a) to pattern (c). The number of plot points and the darker points decreased frompattern (a) to pattern (c). As the class boundary values increased, the number of plot
points decreased and the plot point color became whitish, and vice versa. By setting
appropriate threshold values researchers can highlight the TLCI characteristics that
support their interpretation.
Figure 6 shows the results of a feldspar TLCI analysis with the BP included-type andthe BP excluded-type. The class boundary values used to set the plot colors were 1, 0.1,

10Advanced Java-based application to process thermoluminescence digital color images

Fig. 6 Results of TLCI analysis with (a) the BP included-type and (b) the BP excluded-type. The
analyzed TLCI are from feldspar (Fig. 2(c)). The class boundary values to set the plot colors were 1, 0.1,
0.05, 0.01 and 0.001%.

0.05, 0.01 and 0.001%. A higher number of plot points and dark points were obtained
for the BP excluded-type (Fig. 6(b)) for the BP excluded-type removes black pixels (R+
G+B < 30) in this Java application. The BP excluded-type only evaluates colored pixels
and, therefore, results obtained using the BP excluded-type are independent of theamount of black (or luminescent) pixels in the analyzed image. The BP excluded-type
may be useful to obtain information on combinations of luminous minerals. The BP
included-type may be useful when the number (or percentage) of luminous minerals is
discussed.

3 Conclusion
The Java application reported here is able to visually represent thermoluminescencecolor on a CIE chromaticity diagram regardless of the image size. A threshold inresolution of TLCI for a stable result depends on pattern of color distribution in an
observed area, which may vary sample to sample depending on luminescence intensity
and/or particle size of measured sample.
Threshold values for the selection of plot symbol color can be set by the user. Two
methods (with or without black pixels) are available to calculate the value required to
set symbol color. Feldspar TLCI with the size of 695×695 was investigated by various

M. Ogata, N. Hasebe, A. Inagaki, N. Endo

11

analytical setting (Method and threshold value); 1) BP included type and thresholdvalues of 0.1, 0.01, 0.005, 0.001 and 0.0001% (Fig.3(c) and Fig.5(a)); 2) BP included
type and threshold values of 0.5, 0.05, 0.025, 0.005 and 0.0005% (Fig.5(b)); 3) BP
included type and threshold values of 1, 0.1, 0.05, 0.01 and 0.001% (Fig.5(c) and 6(a));4) BP excluded type and threshold of 1, 0.1, 0.05, 0.01 and 0.001% (Fig.4(b) and 6(b)).
Resultant plots on CIE chromaticity diagram are similar regardless of analytical settings.
This suggests that analytical setting of this Java application does not give a significant
bias on the plot and TLCI characteristics of feldspar can be represented by plotting the
pixel information on the CIE chromaticity diagram.
The numerical treatment of TLCI is still possible as was reported by Inagaki et al.
(2010). The application is able to handle many digital TLCI in a short time and is usefulfor statistical color analyses. Additionally, this application can be applied tothermoluminescence digital image analysis, as well as to other image analyses.

Acknowledgements
We thank Dr. Yukihiro Nakano and Dr. Masaaki Sakamoto for kindly helping with 60Co
gamma-ray irradiation at the Kyoto University Research Reactor. We would like toexpress our gratitude to Kazumi Ito for supplying the sample. We also appreciate our
discussions with Haruka Hayashi, Kentaro Ito, Taeko Itono, Kazumasa Miura, Chiaki
Honda and Ayumi Kozaka.

References
A.D. Franklin, W.F. Hornyak, A.A. Tschirgi, 1988. Thermoluminescence dating of tertiary period
calcite. Quaternary Science Reviews, Vol.7, 361-365.
Y. Ganzawa, K. Kubokita, 2001. Research on the Origin of Eolian Clay Deposits by Means ofThermoluminescence Color Image (TLCI) and Color Image Analysis (TLCI-CIA) Using Quartz
Particles. The Quaternary Research, 40(5), 403-413 [published in Japanese].
Y. Ganzawa, M. Ike, 2011. SAR-RTL dating of single grains of volcanic quartz from the late
Pleistocence Toya Caldera. Quaternary Geochronology, 6, 42-49.
N. Hasebe, A.Inagaki, N. Endo, K. Fukushi, K. Ito, K. Kashiwaya, 2012. Thermoluminescence color
image analysis of sediments from Lake Khuvsgul, Mongolia, and its potential to investigate
paleoenvironmental change. Quaternary Geochronology, 10, 156-159.
T. Hashimoto, Y. Hayashi, A. Koyanagi, K. Yokosaka, K. Kimura, 1986a. Resd and blue colourationof thermoluminescence from natural quartz sands. Nucl. Tracks Radiat. Meas., 11, 229-235.
T. Hashimoto, A. Koyanagi, K. Yokosaka, Y. Hayashi, T. Sotobayashi, 1986b. Thermoluminescencecolor images from quartzs of beach sands. Geochemical Journal, Vol. 20, 111-118.
T. Hashimoto, K. Yokosaka, H. Habuki, Y. Hayashi, 1989. Provenance search of dune sands using
thermoluminescence colour images (TLCIs) from quartz grains. Nucl. Tracks Radiat. Meas, 16,
1, 3-10.

12Advanced Java-based application to process thermoluminescence digital color images

A. Inagaki, N. Hasebe, N. Endo, K. Ito, 2010. Thermoluminescence digital color images and theirevaluation using a Java-based application. Jour, Geol, Soc. Japan, Vol. 116, No. 12, 690-693[published in Japanese].
I. Liritzis, P. Guibert, F. Foti, M. Schvoerer, 1996. Solar bleaching of thermoluminescence of calcites.
Nuclear Instruments and Methods in Physics Research, B 117, 260-268.