Abstract

Diamond clarity refers to the absence of tiny, natural inclusions (imperfections) inside a diamond or on its surface. Almost all diamonds contain their own unique inclusions due to their natural formation process. In this paper, a new inclusion extraction approach is developed to accurately separate the regions of interest in a diamond clarity image and then identify the image features of each region. The inclusion regions can be successfully distinguished from other types of signals. The findings of the theoretical optical analysis facilitate the image processing development and also reduce its complexity and operation time. The experimental results verify the effectiveness and robustness of the proposed inclusion extraction approach. The diamond inclusions can be accurately extracted from the captured diamond clarity image. The extracted inclusions can also be converted to their actual size as seen by the naked human eye. The proposed approach is verified to be significantly less sensitive to noise than existing approaches and unaffected by the fluctuations in illumination.

© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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References

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  1. Renee Newman, Diamond handbook: How to identify & Evaluate diamond (International Jewelry Publications, 2018).
  2. Verena Pagel-Theisen, Diamond Grading ABC: Handbook for Diamond Grading (Pagel-Theisen, 1990).
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    [Crossref]
  8. Nobuyuki Otsu, "A threshold selection method from gray-level histograms," Automatica 11, 285–296 (1975).
  9. Holger Schwenk and Yoshua Bengio, "Training Methods for Adaptive Boosting of Neural Networks for Character Recognition," Neural Inf. Process Syst., 9, 647–653 (2001).
  10. Xuchun Li, Lei Wang, and Eric Sung, "AdaBoost with SVM-based component classifiers," Eng. Appl. Artif. Intell., 21, 785–795 (2008).
    [Crossref]
  11. Juan Mauricio, "Implementing a deep learning algorithm for diamond classification," Florida International U. (2018).
  12. R Berman, Physical Properties of Diamond(Clarendon Press, 1965).
  13. M. Tolkowsky, "Diamond Design: A Study of the Reflection and Refraction of Light in a Diamond," E. & F.N. Spon, (1919).
  14. G. E. Harlow, The Nature of Diamonds(Cambridge U. Press, 1997).
  15. Ljubisa R. Radovic, Chemistry & Physics of Carbon(CRC Press, 2012).
    [Crossref]
  16. Roshan L. Aggarwal and Anant K. Ramdas, Physical Properties of Diamond and Sapphire(CRC Press, 2019).
    [Crossref]
  17. Rafael C. Gonzalez and Richard E. Woods, Digital Image Processing (Pearson Education Inc., 2007).
  18. M. Sonka, V. Hlavac, and R. Boyle, Analysis and Machine Vision(Springer, 1993).
  19. S Krig, Computer Vision Metrics: Survey, Taxonomy, and Analysis (Apress, 2014).
    [Crossref]
  20. Anthony A. Tanbakuchi, Arjen van der Sijde, Bart Dillen, Albert Theuwissen, and Wim de Haan, "Adaptive pixel defect correction," Proc. SPIE 5017, 360 (2003).
  21. Andrzej Kordecki, Henryk Palus, and Artur Bal, "Practical vignetting correction method for digital camera with measurement of surface luminance distribution," Sig. Im. a Vid. Pro., 10, 1417–1424 (2016).
  22. Yuanjie Zheng, Stephen Lin, Chandra Kambhamettu, Jingyi Yu, and Sing Bing Kang, "Single-Image Vignetting Correction," TPAMI, 31, 2243–2256 (2009).
    [Crossref]
  23. Baxes Gregory, Digital Image Processing: Principles and Applications (Wiley, 1994).
  24. Yadong Wu, Zhiqin Liu, Yongguo Han, and Hongying Zhang, "An image illumination correction algorithm based on tone mapping," in 3rd International Congress on Image and Signal Processing (2010), pp. 645–648.
  25. Somyinig Thaininiit and Chee-Hing Henry Chu, "Illumination correction in digital images," IEEE T. Inf. Foren. Sec., 4, 7803–7970 (2003).
  26. G. Healey and R. Kondepudy, "Radiometric CCD camera calibration and noise estimation," TPAMI, 16, 267–276 (1994).
    [Crossref]
  27. X. Pan and S. Lyu, "Region Duplication Detection Using Image Feature Matching," IEEE T. In. Foren. Sec., 5, 857–867 (2010).
    [Crossref]

2016 (1)

Andrzej Kordecki, Henryk Palus, and Artur Bal, "Practical vignetting correction method for digital camera with measurement of surface luminance distribution," Sig. Im. a Vid. Pro., 10, 1417–1424 (2016).

2010 (1)

X. Pan and S. Lyu, "Region Duplication Detection Using Image Feature Matching," IEEE T. In. Foren. Sec., 5, 857–867 (2010).
[Crossref]

2009 (1)

Yuanjie Zheng, Stephen Lin, Chandra Kambhamettu, Jingyi Yu, and Sing Bing Kang, "Single-Image Vignetting Correction," TPAMI, 31, 2243–2256 (2009).
[Crossref]

2008 (1)

Xuchun Li, Lei Wang, and Eric Sung, "AdaBoost with SVM-based component classifiers," Eng. Appl. Artif. Intell., 21, 785–795 (2008).
[Crossref]

2003 (2)

Anthony A. Tanbakuchi, Arjen van der Sijde, Bart Dillen, Albert Theuwissen, and Wim de Haan, "Adaptive pixel defect correction," Proc. SPIE 5017, 360 (2003).

Somyinig Thaininiit and Chee-Hing Henry Chu, "Illumination correction in digital images," IEEE T. Inf. Foren. Sec., 4, 7803–7970 (2003).

2001 (1)

Holger Schwenk and Yoshua Bengio, "Training Methods for Adaptive Boosting of Neural Networks for Character Recognition," Neural Inf. Process Syst., 9, 647–653 (2001).

1994 (1)

G. Healey and R. Kondepudy, "Radiometric CCD camera calibration and noise estimation," TPAMI, 16, 267–276 (1994).
[Crossref]

1986 (1)

J. Canny, "A Computational Approach to Edge Detection," TPAMI, 8, 679–698 (1986).
[Crossref]

1975 (1)

Nobuyuki Otsu, "A threshold selection method from gray-level histograms," Automatica 11, 285–296 (1975).

Aggarwal, Roshan L.

Roshan L. Aggarwal and Anant K. Ramdas, Physical Properties of Diamond and Sapphire(CRC Press, 2019).
[Crossref]

Bal, Artur

Andrzej Kordecki, Henryk Palus, and Artur Bal, "Practical vignetting correction method for digital camera with measurement of surface luminance distribution," Sig. Im. a Vid. Pro., 10, 1417–1424 (2016).

Bengio, Yoshua

Holger Schwenk and Yoshua Bengio, "Training Methods for Adaptive Boosting of Neural Networks for Character Recognition," Neural Inf. Process Syst., 9, 647–653 (2001).

Berman, R

R Berman, Physical Properties of Diamond(Clarendon Press, 1965).

Blodgett, T.

M. Verboven, T. Blodgett, and D. Nuyts, "Automated system and method for clarity measurement and clarity grading," https://patents.google.com/patent/US20100086179A1/en US Patent2010/0086179 (April24, 2010).

Boyle, R.

M. Sonka, V. Hlavac, and R. Boyle, Analysis and Machine Vision(Springer, 1993).

Canny, J.

J. Canny, "A Computational Approach to Edge Detection," TPAMI, 8, 679–698 (1986).
[Crossref]

Chu, Chee-Hing Henry

Somyinig Thaininiit and Chee-Hing Henry Chu, "Illumination correction in digital images," IEEE T. Inf. Foren. Sec., 4, 7803–7970 (2003).

de Haan, Wim

Anthony A. Tanbakuchi, Arjen van der Sijde, Bart Dillen, Albert Theuwissen, and Wim de Haan, "Adaptive pixel defect correction," Proc. SPIE 5017, 360 (2003).

Dillen, Bart

Anthony A. Tanbakuchi, Arjen van der Sijde, Bart Dillen, Albert Theuwissen, and Wim de Haan, "Adaptive pixel defect correction," Proc. SPIE 5017, 360 (2003).

Gonzalez, Rafael C.

Rafael C. Gonzalez and Richard E. Woods, Digital Image Processing (Pearson Education Inc., 2007).

Gregory, Baxes

Baxes Gregory, Digital Image Processing: Principles and Applications (Wiley, 1994).

Han, Yongguo

Yadong Wu, Zhiqin Liu, Yongguo Han, and Hongying Zhang, "An image illumination correction algorithm based on tone mapping," in 3rd International Congress on Image and Signal Processing (2010), pp. 645–648.

Harlow, G. E.

G. E. Harlow, The Nature of Diamonds(Cambridge U. Press, 1997).

Healey, G.

G. Healey and R. Kondepudy, "Radiometric CCD camera calibration and noise estimation," TPAMI, 16, 267–276 (1994).
[Crossref]

Hlavac, V.

M. Sonka, V. Hlavac, and R. Boyle, Analysis and Machine Vision(Springer, 1993).

Kambhamettu, Chandra

Yuanjie Zheng, Stephen Lin, Chandra Kambhamettu, Jingyi Yu, and Sing Bing Kang, "Single-Image Vignetting Correction," TPAMI, 31, 2243–2256 (2009).
[Crossref]

Kang, Sing Bing

Yuanjie Zheng, Stephen Lin, Chandra Kambhamettu, Jingyi Yu, and Sing Bing Kang, "Single-Image Vignetting Correction," TPAMI, 31, 2243–2256 (2009).
[Crossref]

Kondepudy, R.

G. Healey and R. Kondepudy, "Radiometric CCD camera calibration and noise estimation," TPAMI, 16, 267–276 (1994).
[Crossref]

Kordecki, Andrzej

Andrzej Kordecki, Henryk Palus, and Artur Bal, "Practical vignetting correction method for digital camera with measurement of surface luminance distribution," Sig. Im. a Vid. Pro., 10, 1417–1424 (2016).

Krig, S

S Krig, Computer Vision Metrics: Survey, Taxonomy, and Analysis (Apress, 2014).
[Crossref]

Li, Xuchun

Xuchun Li, Lei Wang, and Eric Sung, "AdaBoost with SVM-based component classifiers," Eng. Appl. Artif. Intell., 21, 785–795 (2008).
[Crossref]

Lin, Stephen

Yuanjie Zheng, Stephen Lin, Chandra Kambhamettu, Jingyi Yu, and Sing Bing Kang, "Single-Image Vignetting Correction," TPAMI, 31, 2243–2256 (2009).
[Crossref]

Liu, Zhiqin

Yadong Wu, Zhiqin Liu, Yongguo Han, and Hongying Zhang, "An image illumination correction algorithm based on tone mapping," in 3rd International Congress on Image and Signal Processing (2010), pp. 645–648.

Lyu, S.

X. Pan and S. Lyu, "Region Duplication Detection Using Image Feature Matching," IEEE T. In. Foren. Sec., 5, 857–867 (2010).
[Crossref]

Mauricio, Juan

Juan Mauricio, "Implementing a deep learning algorithm for diamond classification," Florida International U. (2018).

Newman, Renee

Renee Newman, Diamond handbook: How to identify & Evaluate diamond (International Jewelry Publications, 2018).

Renee Newman, Diamond Handbook: A Practical Guide to Diamond Evaluation (International Jewelry Publications, 2010).

Nuyts, D.

M. Verboven, T. Blodgett, and D. Nuyts, "Automated system and method for clarity measurement and clarity grading," https://patents.google.com/patent/US20100086179A1/en US Patent2010/0086179 (April24, 2010).

Otsu, Nobuyuki

Nobuyuki Otsu, "A threshold selection method from gray-level histograms," Automatica 11, 285–296 (1975).

Palus, Henryk

Andrzej Kordecki, Henryk Palus, and Artur Bal, "Practical vignetting correction method for digital camera with measurement of surface luminance distribution," Sig. Im. a Vid. Pro., 10, 1417–1424 (2016).

Pan, X.

X. Pan and S. Lyu, "Region Duplication Detection Using Image Feature Matching," IEEE T. In. Foren. Sec., 5, 857–867 (2010).
[Crossref]

Radovic, Ljubisa R.

Ljubisa R. Radovic, Chemistry & Physics of Carbon(CRC Press, 2012).
[Crossref]

Ramdas, Anant K.

Roshan L. Aggarwal and Anant K. Ramdas, Physical Properties of Diamond and Sapphire(CRC Press, 2019).
[Crossref]

Schwenk, Holger

Holger Schwenk and Yoshua Bengio, "Training Methods for Adaptive Boosting of Neural Networks for Character Recognition," Neural Inf. Process Syst., 9, 647–653 (2001).

Song, Lin

Lin Song, "A method of automatic cut grading for round diamond", MPhi. Thesis, Department of Mechanical and Aerospace Engineering, The Hong Kong University of Science and Technology (2011).

Sonka, M.

M. Sonka, V. Hlavac, and R. Boyle, Analysis and Machine Vision(Springer, 1993).

Sung, Eric

Xuchun Li, Lei Wang, and Eric Sung, "AdaBoost with SVM-based component classifiers," Eng. Appl. Artif. Intell., 21, 785–795 (2008).
[Crossref]

Tanbakuchi, Anthony A.

Anthony A. Tanbakuchi, Arjen van der Sijde, Bart Dillen, Albert Theuwissen, and Wim de Haan, "Adaptive pixel defect correction," Proc. SPIE 5017, 360 (2003).

Thaininiit, Somyinig

Somyinig Thaininiit and Chee-Hing Henry Chu, "Illumination correction in digital images," IEEE T. Inf. Foren. Sec., 4, 7803–7970 (2003).

Theuwissen, Albert

Anthony A. Tanbakuchi, Arjen van der Sijde, Bart Dillen, Albert Theuwissen, and Wim de Haan, "Adaptive pixel defect correction," Proc. SPIE 5017, 360 (2003).

Tolkowsky, M.

M. Tolkowsky, "Diamond Design: A Study of the Reflection and Refraction of Light in a Diamond," E. & F.N. Spon, (1919).

van der Sijde, Arjen

Anthony A. Tanbakuchi, Arjen van der Sijde, Bart Dillen, Albert Theuwissen, and Wim de Haan, "Adaptive pixel defect correction," Proc. SPIE 5017, 360 (2003).

Verboven, M.

M. Verboven, T. Blodgett, and D. Nuyts, "Automated system and method for clarity measurement and clarity grading," https://patents.google.com/patent/US20100086179A1/en US Patent2010/0086179 (April24, 2010).

Wang, Lei

Xuchun Li, Lei Wang, and Eric Sung, "AdaBoost with SVM-based component classifiers," Eng. Appl. Artif. Intell., 21, 785–795 (2008).
[Crossref]

Woods, Richard E.

Rafael C. Gonzalez and Richard E. Woods, Digital Image Processing (Pearson Education Inc., 2007).

Wu, Yadong

Yadong Wu, Zhiqin Liu, Yongguo Han, and Hongying Zhang, "An image illumination correction algorithm based on tone mapping," in 3rd International Congress on Image and Signal Processing (2010), pp. 645–648.

Yu, Jingyi

Yuanjie Zheng, Stephen Lin, Chandra Kambhamettu, Jingyi Yu, and Sing Bing Kang, "Single-Image Vignetting Correction," TPAMI, 31, 2243–2256 (2009).
[Crossref]

Zhang, Hongying

Yadong Wu, Zhiqin Liu, Yongguo Han, and Hongying Zhang, "An image illumination correction algorithm based on tone mapping," in 3rd International Congress on Image and Signal Processing (2010), pp. 645–648.

Zheng, Yuanjie

Yuanjie Zheng, Stephen Lin, Chandra Kambhamettu, Jingyi Yu, and Sing Bing Kang, "Single-Image Vignetting Correction," TPAMI, 31, 2243–2256 (2009).
[Crossref]

Automatica (1)

Nobuyuki Otsu, "A threshold selection method from gray-level histograms," Automatica 11, 285–296 (1975).

Eng. Appl. Artif. Intell. (1)

Xuchun Li, Lei Wang, and Eric Sung, "AdaBoost with SVM-based component classifiers," Eng. Appl. Artif. Intell., 21, 785–795 (2008).
[Crossref]

IEEE T. In. Foren. Sec. (1)

X. Pan and S. Lyu, "Region Duplication Detection Using Image Feature Matching," IEEE T. In. Foren. Sec., 5, 857–867 (2010).
[Crossref]

IEEE T. Inf. Foren. Sec. (1)

Somyinig Thaininiit and Chee-Hing Henry Chu, "Illumination correction in digital images," IEEE T. Inf. Foren. Sec., 4, 7803–7970 (2003).

Neural Inf. Process Syst. (1)

Holger Schwenk and Yoshua Bengio, "Training Methods for Adaptive Boosting of Neural Networks for Character Recognition," Neural Inf. Process Syst., 9, 647–653 (2001).

Proc. SPIE (1)

Anthony A. Tanbakuchi, Arjen van der Sijde, Bart Dillen, Albert Theuwissen, and Wim de Haan, "Adaptive pixel defect correction," Proc. SPIE 5017, 360 (2003).

Sig. Im. a Vid. Pro. (1)

Andrzej Kordecki, Henryk Palus, and Artur Bal, "Practical vignetting correction method for digital camera with measurement of surface luminance distribution," Sig. Im. a Vid. Pro., 10, 1417–1424 (2016).

TPAMI (3)

Yuanjie Zheng, Stephen Lin, Chandra Kambhamettu, Jingyi Yu, and Sing Bing Kang, "Single-Image Vignetting Correction," TPAMI, 31, 2243–2256 (2009).
[Crossref]

G. Healey and R. Kondepudy, "Radiometric CCD camera calibration and noise estimation," TPAMI, 16, 267–276 (1994).
[Crossref]

J. Canny, "A Computational Approach to Edge Detection," TPAMI, 8, 679–698 (1986).
[Crossref]

Other (17)

Baxes Gregory, Digital Image Processing: Principles and Applications (Wiley, 1994).

Yadong Wu, Zhiqin Liu, Yongguo Han, and Hongying Zhang, "An image illumination correction algorithm based on tone mapping," in 3rd International Congress on Image and Signal Processing (2010), pp. 645–648.

Renee Newman, Diamond handbook: How to identify & Evaluate diamond (International Jewelry Publications, 2018).

Verena Pagel-Theisen, Diamond Grading ABC: Handbook for Diamond Grading (Pagel-Theisen, 1990).

GIA Diamond Grading Lab Manual (Gemological Institute of America, 2006).

Renee Newman, Diamond Handbook: A Practical Guide to Diamond Evaluation (International Jewelry Publications, 2010).

M. Verboven, T. Blodgett, and D. Nuyts, "Automated system and method for clarity measurement and clarity grading," https://patents.google.com/patent/US20100086179A1/en US Patent2010/0086179 (April24, 2010).

Lin Song, "A method of automatic cut grading for round diamond", MPhi. Thesis, Department of Mechanical and Aerospace Engineering, The Hong Kong University of Science and Technology (2011).

Juan Mauricio, "Implementing a deep learning algorithm for diamond classification," Florida International U. (2018).

R Berman, Physical Properties of Diamond(Clarendon Press, 1965).

M. Tolkowsky, "Diamond Design: A Study of the Reflection and Refraction of Light in a Diamond," E. & F.N. Spon, (1919).

G. E. Harlow, The Nature of Diamonds(Cambridge U. Press, 1997).

Ljubisa R. Radovic, Chemistry & Physics of Carbon(CRC Press, 2012).
[Crossref]

Roshan L. Aggarwal and Anant K. Ramdas, Physical Properties of Diamond and Sapphire(CRC Press, 2019).
[Crossref]

Rafael C. Gonzalez and Richard E. Woods, Digital Image Processing (Pearson Education Inc., 2007).

M. Sonka, V. Hlavac, and R. Boyle, Analysis and Machine Vision(Springer, 1993).

S Krig, Computer Vision Metrics: Survey, Taxonomy, and Analysis (Apress, 2014).
[Crossref]

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Figures (11)

Fig. 1
Fig. 1 The diamond image in Lin’s thesis [6] before and after applying the Canny edge detector and the Otsu threshold searching approach.
Fig. 2
Fig. 2 Example of how a light ray passes from air into a diamond and is finally refracted out into the air again.
Fig. 3
Fig. 3 Diffused reflection from the diamond inclusion and the irregular shape of the inclusion curve.
Fig. 4
Fig. 4 Schematic diagram showing the light path within the diamond inclusion image acquisition system.
Fig. 5
Fig. 5 Block diagram of the image processing steps for diamond inclusion extraction.
Fig. 6
Fig. 6 Original captured images of the inspected diamond sample. (a) An example of a diamond that is sitting on the sample loading glass at an angle. (b) An example of a diamond that is correctly placed with the table facet facing down.
Fig. 7
Fig. 7 Diamond clarity images before (7(a)) and after (7(b)) the enhancement operation.
Fig. 8
Fig. 8 (a) Regions of interest extracted from Fig. 7(b) marked with red curves. (b) Intersections detected in Fig. 7(b) marked with red dots.
Fig. 9
Fig. 9 (a) Extracted inclusion regions of the diamond clarity image (b) Extracted reflection regions of the diamond clarity image.
Fig. 10
Fig. 10 Experimental results of diamond inclusion extraction. (Left) Captured clarity image of an inspected diamond sample. (Right) Extracted inclusion regions.
Fig. 11
Fig. 11 Experimental results of the same diamond sample under different illumination intensity and placement direction. (Left) The captured clarity image of an inspected diamond sample (Right) The extracted inclusion regions.

Tables (1)

Tables Icon

Table 1 Consistency Between the Results Obtained by the Diamond Inclusion Extraction Approach and Manual Inclusion Detection.

Equations (20)

Equations on this page are rendered with MathJax. Learn more.

θ c = sin 1 n t n i
r = E r E i , t = E r E i
r = n i cos ( θ i ) n t cos ( θ t ) n i cos ( θ i ) + n t cos ( θ t ) , r = n i cos ( θ t ) n t cos ( θ i ) n i cos ( θ t ) + n t cos ( θ i )
t = 2 n i cos ( θ i ) n i cos ( θ i ) + n t cos ( θ t ) , t = 2 n i cos ( θ i ) n i cos ( θ t ) + n t cos ( θ i )
n i sin ( θ i ) = n t sin ( θ t )
r = sin ( θ i θ t ) sin ( θ i + θ t ) , r = tan ( θ i θ t ) tan ( θ i + θ t )
t = 2 sin θ t cos θ i sin ( θ i + θ t ) , t = 2 sin θ t cos θ i sin ( θ i + θ t ) cos ( θ i θ t )
R = | E r | 2 | E i | 2 = | r | 2
T = n 2 cos θ t n 1 cos θ i | E t | 2 | E i | 2 = n 2 cos θ t n 1 cos θ i | t | 2
h f > E g
E g max = h c λ min = 3.18 e V , E g min = h c λ max = 1.77 e V
T max = ( 1 R ) 2 1 R 2 = 70.65 %
S N R = x = 0 m 1 y = 0 n 1 f ^ ( x , y ) 2 x = 0 m 1 y = 0 n 1 [ f ( x , y ) f ^ ( x , y ) ] 2
Δ r m s = [ 1 m n i = 0 m 1 j = 0 n 1 [ O ( i , j ) I ( i , j ) ] 2 ] 1 / 2
E ( u , v ) = x , y w ( x , y ) [ I ( x + u , y + v ) I ( x , y ) ] 2
E ( u , v ) [ u v ] M [ u v ]
M = x , y w ( x , y ) [ I x I x I x I y I x I y I y I y ]
R = d e t ( M ) k ( t r a c e ( M ) ) 2
det ( M ) = λ 1 λ 2 t r a c e ( M )
S a = S z × N p = L p × N p / M

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