Abstract

A three-color mixing application for food safety inspection is presented. It is shown that the chromaticness of the visual signal resulting from the three-color mixing achieved through our device is directly related to the three-band ratio of light intensity at three selected wavebands. An optical visual device using three-color mixing to implement the three-band ratio criterion is presented. Inspection through human vision assisted by an optical device that implements the three-band ratio criterion would offer flexibility and significant cost savings as compared to inspection with a multispectral machine vision system that implements the same criterion. Example applications of this optical three-color mixing technique are given for the inspection of chicken carcasses with various diseases and for apples with fecal contamination. With proper selection of the three narrow wavebands, discrimination by chromaticness that has a direct relation with the three-band ratio can work very well. In particular, compared with the previously presented two-color mixing application, the conditions of chicken carcasses were more easily identified using the three-color mixing application. The novel three-color mixing technique for visual inspection can be implemented on visual devices for a variety of applications, ranging from target detection to food safety inspection.

© 2006 Optical Society of America

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  1. Y. R. Chen, K. Chao, and M. S. Kim, "Machine vision technology for agricultural applications," Comput. Electron. Agric. 36 (2), 173-191 (2002).
    [CrossRef]
  2. Y. R. Chen and W. R. Hruschka, "On-line trials of a chicken carcass inspection system using visible/near-infrared reflectance," presented at the 1998 ASAE Annual International Meeting, Orlando, Fla., 12-15 July 1998, paper 983047.
  3. Y. R. Chen and D. R. Massie, "Visible/NIR reflectance and interactance spectroscopy for detection poultry carcasses," Trans. ASAE 36, 863-869 (1993).
  4. Y.-R. Chen, "Classifying diseased poultry carcasses by visible and near-IR reflectance spectroscopy," Optics in Agriculture and Forestry, J.A.Deshazer and G.E.Meyer, eds., Proc. SPIE 1836, 44-55 (1992).
  5. K. Chao, Y. R. Chen, W. R. Hruschka, and F. B. Gwozdz, "On-line inspection of poultry carcasses by dual-camera system," J. Food Engr. 51 (3), 185-192 (2002).
    [CrossRef]
  6. M. S. Kim, A. M. Lefcourt, and Y. R. Chen, "Multispectral laser-induced fluorescence imaging system for large biological samples," Appl. Opt. 42, 3927-3934 (2003).
  7. A. M. Lefcourt, M. S. Kim, and Y. R. Chen, "Automated detection of fecal contamination of apples by multispectral laser-induced fluorescence imaging," Appl. Opt. 42, 3935-3943 (2003).
  8. R. Pu, S. Ge, N. M. Kelly, and P. Gong, "Spectral absorption features as indicators of water status in coast live oak (Quercus agrifolia) leaves, Intl. J. Remote Sens. 24, 1799-1810 (2003).
    [CrossRef]
  9. S. C. Liew, A. S. Chia, and L. K. Kwoh, "Evaluating the validity of SeaWifs chlorophyll algorithm for coastal waters," presented at the 22nd Asian Conference on Remote Sensing, Singapore, 5-9 November2001.
  10. R. N. Clark, A. J. Gallagher, and G. A. Swayze, "Material absorption band depth mapping of imaging spectrometer data using a complete band shape least-squares fit with library reference spectra," JPL Publ. 90-54, 176-186 (1990).
  11. R. F. Kokaly and R. N. Clark, "Spectroscopic determination of leaf biochemistry using band-depth analysis of absorption features and stepwise linear regression," Remote Sensing Environ. 67, 267-287 (1999).
    [CrossRef]
  12. R. E. Feind and R. M. Welch, "Cloud fraction and cloud shadow property retrievals from coregistered TIMS and AVIRIS imagery: the use of cloud morphology for registration," IEEE Trans. Geosci. Remote Sens. 33, 172-184 (1995).
    [CrossRef]
  13. B. C. Gao and A. F. Goetz, "Extraction of dry leaf spectral features from reflectance spectra of green vegetation," Remote Sens. Environ. 47, 369-274 (1994).
    [CrossRef]
  14. Y. R. Chen, B. Park, R. W. Huffman, and M. Nguyen, "Classification of on-line poultry carcasses with backpropagation neural networks," J. Food Proc. Engr. 21(1), 33-48 (1998).
  15. P. M. Mehl, Y. R. Chen, M. S. Kim, and D. E. Chan "Development of hyperspectral imaging technique for the detection of apple surface detects and contaminations," J. Food Engr. 61, 67-81 (2004).
    [CrossRef]
  16. R. Lu and Y. R. Chen, "Hyperspectral imaging for safety inspection of food and agricultural products," in Pathogen Detection and Remediation for Safe Eating, Y.-R.Chen, ed., Proc. SPIE 3544, 121-133 (1998).
  17. F. Ding, Y. R. Chen, and K. Chao, "Two-waveband color-mixing binoculars for the detection of wholesome and unwholesome chicken carcasses: a simulation," Appl. Opt. 44, 5454-5462 (2005).
    [CrossRef]
  18. F. Ding, Y. R. Chen, K. Chao, and D. E. Chan, "Two-color mixing for classifying agricultural products for safety and quality," Appl. Opt. 45, 668-677 (2006).
    [CrossRef]
  19. F. Ding, Y. R. Chen, and K. Chao, "Application of color mixing for safety and quality inspection of agricultural products," in Optical Sensors and Sensing Systems for Natural Resources and Food Safety and Quality, Y.-R, Chen, G.E.Meyer, and S.-I.Tu, eds., Proc. SPIE5996, 59960R (2005).
  20. M. Vriesenga, "Colored illumination for enhancing discriminability in machine vision," J. Visual Commun. Image Represent.6(3), 244-255 (1995).
  21. G. Wyszecki and W. S. Stiles, Color Science: Concepts and Methods, Quantitative Data and Formulas (Wiley, 1982).
  22. C. J. Li, M. R. Luo, and R. W. G. Hunt, "A revision of CIECAM97s model," Color Res. Appl. 25, 260-266 (2000).
    [CrossRef]
  23. M. D. Fairchild, "Revision of CIECAM97s for practical applications," Color Res. Appl. 26, 418-427 (2001).
    [CrossRef]
  24. B. P. Dey, Y. R. Chen, C. Hsieh, and D. E. Chan, "Detection of septicemia in chicken livers by spectroscopy," Poultry Sci. 82, 199-206 (2003).
  25. International Commission on Illumination, "Recommendation on uniform color spaces, color difference equations, psychometric color terms," Suppl. 2 to CIE Publ. 15 (E.-1.3.1), 1971/(TC-1.3.) (CIE, 1978).

2006 (1)

2005 (2)

F. Ding, Y. R. Chen, and K. Chao, "Two-waveband color-mixing binoculars for the detection of wholesome and unwholesome chicken carcasses: a simulation," Appl. Opt. 44, 5454-5462 (2005).
[CrossRef]

F. Ding, Y. R. Chen, and K. Chao, "Application of color mixing for safety and quality inspection of agricultural products," in Optical Sensors and Sensing Systems for Natural Resources and Food Safety and Quality, Y.-R, Chen, G.E.Meyer, and S.-I.Tu, eds., Proc. SPIE5996, 59960R (2005).

2004 (1)

P. M. Mehl, Y. R. Chen, M. S. Kim, and D. E. Chan "Development of hyperspectral imaging technique for the detection of apple surface detects and contaminations," J. Food Engr. 61, 67-81 (2004).
[CrossRef]

2003 (4)

R. Pu, S. Ge, N. M. Kelly, and P. Gong, "Spectral absorption features as indicators of water status in coast live oak (Quercus agrifolia) leaves, Intl. J. Remote Sens. 24, 1799-1810 (2003).
[CrossRef]

B. P. Dey, Y. R. Chen, C. Hsieh, and D. E. Chan, "Detection of septicemia in chicken livers by spectroscopy," Poultry Sci. 82, 199-206 (2003).

M. S. Kim, A. M. Lefcourt, and Y. R. Chen, "Multispectral laser-induced fluorescence imaging system for large biological samples," Appl. Opt. 42, 3927-3934 (2003).

A. M. Lefcourt, M. S. Kim, and Y. R. Chen, "Automated detection of fecal contamination of apples by multispectral laser-induced fluorescence imaging," Appl. Opt. 42, 3935-3943 (2003).

2002 (2)

K. Chao, Y. R. Chen, W. R. Hruschka, and F. B. Gwozdz, "On-line inspection of poultry carcasses by dual-camera system," J. Food Engr. 51 (3), 185-192 (2002).
[CrossRef]

Y. R. Chen, K. Chao, and M. S. Kim, "Machine vision technology for agricultural applications," Comput. Electron. Agric. 36 (2), 173-191 (2002).
[CrossRef]

2001 (2)

S. C. Liew, A. S. Chia, and L. K. Kwoh, "Evaluating the validity of SeaWifs chlorophyll algorithm for coastal waters," presented at the 22nd Asian Conference on Remote Sensing, Singapore, 5-9 November2001.

M. D. Fairchild, "Revision of CIECAM97s for practical applications," Color Res. Appl. 26, 418-427 (2001).
[CrossRef]

2000 (1)

C. J. Li, M. R. Luo, and R. W. G. Hunt, "A revision of CIECAM97s model," Color Res. Appl. 25, 260-266 (2000).
[CrossRef]

1999 (1)

R. F. Kokaly and R. N. Clark, "Spectroscopic determination of leaf biochemistry using band-depth analysis of absorption features and stepwise linear regression," Remote Sensing Environ. 67, 267-287 (1999).
[CrossRef]

1998 (2)

R. Lu and Y. R. Chen, "Hyperspectral imaging for safety inspection of food and agricultural products," in Pathogen Detection and Remediation for Safe Eating, Y.-R.Chen, ed., Proc. SPIE 3544, 121-133 (1998).

Y. R. Chen, B. Park, R. W. Huffman, and M. Nguyen, "Classification of on-line poultry carcasses with backpropagation neural networks," J. Food Proc. Engr. 21(1), 33-48 (1998).

1995 (2)

M. Vriesenga, "Colored illumination for enhancing discriminability in machine vision," J. Visual Commun. Image Represent.6(3), 244-255 (1995).

R. E. Feind and R. M. Welch, "Cloud fraction and cloud shadow property retrievals from coregistered TIMS and AVIRIS imagery: the use of cloud morphology for registration," IEEE Trans. Geosci. Remote Sens. 33, 172-184 (1995).
[CrossRef]

1994 (1)

B. C. Gao and A. F. Goetz, "Extraction of dry leaf spectral features from reflectance spectra of green vegetation," Remote Sens. Environ. 47, 369-274 (1994).
[CrossRef]

1993 (1)

Y. R. Chen and D. R. Massie, "Visible/NIR reflectance and interactance spectroscopy for detection poultry carcasses," Trans. ASAE 36, 863-869 (1993).

1992 (1)

Y.-R. Chen, "Classifying diseased poultry carcasses by visible and near-IR reflectance spectroscopy," Optics in Agriculture and Forestry, J.A.Deshazer and G.E.Meyer, eds., Proc. SPIE 1836, 44-55 (1992).

1990 (1)

R. N. Clark, A. J. Gallagher, and G. A. Swayze, "Material absorption band depth mapping of imaging spectrometer data using a complete band shape least-squares fit with library reference spectra," JPL Publ. 90-54, 176-186 (1990).

1982 (1)

G. Wyszecki and W. S. Stiles, Color Science: Concepts and Methods, Quantitative Data and Formulas (Wiley, 1982).

1978 (1)

International Commission on Illumination, "Recommendation on uniform color spaces, color difference equations, psychometric color terms," Suppl. 2 to CIE Publ. 15 (E.-1.3.1), 1971/(TC-1.3.) (CIE, 1978).

Chan, D. E.

F. Ding, Y. R. Chen, K. Chao, and D. E. Chan, "Two-color mixing for classifying agricultural products for safety and quality," Appl. Opt. 45, 668-677 (2006).
[CrossRef]

P. M. Mehl, Y. R. Chen, M. S. Kim, and D. E. Chan "Development of hyperspectral imaging technique for the detection of apple surface detects and contaminations," J. Food Engr. 61, 67-81 (2004).
[CrossRef]

B. P. Dey, Y. R. Chen, C. Hsieh, and D. E. Chan, "Detection of septicemia in chicken livers by spectroscopy," Poultry Sci. 82, 199-206 (2003).

Chao, K.

F. Ding, Y. R. Chen, K. Chao, and D. E. Chan, "Two-color mixing for classifying agricultural products for safety and quality," Appl. Opt. 45, 668-677 (2006).
[CrossRef]

F. Ding, Y. R. Chen, and K. Chao, "Application of color mixing for safety and quality inspection of agricultural products," in Optical Sensors and Sensing Systems for Natural Resources and Food Safety and Quality, Y.-R, Chen, G.E.Meyer, and S.-I.Tu, eds., Proc. SPIE5996, 59960R (2005).

F. Ding, Y. R. Chen, and K. Chao, "Two-waveband color-mixing binoculars for the detection of wholesome and unwholesome chicken carcasses: a simulation," Appl. Opt. 44, 5454-5462 (2005).
[CrossRef]

Y. R. Chen, K. Chao, and M. S. Kim, "Machine vision technology for agricultural applications," Comput. Electron. Agric. 36 (2), 173-191 (2002).
[CrossRef]

K. Chao, Y. R. Chen, W. R. Hruschka, and F. B. Gwozdz, "On-line inspection of poultry carcasses by dual-camera system," J. Food Engr. 51 (3), 185-192 (2002).
[CrossRef]

Chen, Y. R.

F. Ding, Y. R. Chen, K. Chao, and D. E. Chan, "Two-color mixing for classifying agricultural products for safety and quality," Appl. Opt. 45, 668-677 (2006).
[CrossRef]

F. Ding, Y. R. Chen, and K. Chao, "Application of color mixing for safety and quality inspection of agricultural products," in Optical Sensors and Sensing Systems for Natural Resources and Food Safety and Quality, Y.-R, Chen, G.E.Meyer, and S.-I.Tu, eds., Proc. SPIE5996, 59960R (2005).

F. Ding, Y. R. Chen, and K. Chao, "Two-waveband color-mixing binoculars for the detection of wholesome and unwholesome chicken carcasses: a simulation," Appl. Opt. 44, 5454-5462 (2005).
[CrossRef]

P. M. Mehl, Y. R. Chen, M. S. Kim, and D. E. Chan "Development of hyperspectral imaging technique for the detection of apple surface detects and contaminations," J. Food Engr. 61, 67-81 (2004).
[CrossRef]

A. M. Lefcourt, M. S. Kim, and Y. R. Chen, "Automated detection of fecal contamination of apples by multispectral laser-induced fluorescence imaging," Appl. Opt. 42, 3935-3943 (2003).

B. P. Dey, Y. R. Chen, C. Hsieh, and D. E. Chan, "Detection of septicemia in chicken livers by spectroscopy," Poultry Sci. 82, 199-206 (2003).

M. S. Kim, A. M. Lefcourt, and Y. R. Chen, "Multispectral laser-induced fluorescence imaging system for large biological samples," Appl. Opt. 42, 3927-3934 (2003).

K. Chao, Y. R. Chen, W. R. Hruschka, and F. B. Gwozdz, "On-line inspection of poultry carcasses by dual-camera system," J. Food Engr. 51 (3), 185-192 (2002).
[CrossRef]

Y. R. Chen, K. Chao, and M. S. Kim, "Machine vision technology for agricultural applications," Comput. Electron. Agric. 36 (2), 173-191 (2002).
[CrossRef]

R. Lu and Y. R. Chen, "Hyperspectral imaging for safety inspection of food and agricultural products," in Pathogen Detection and Remediation for Safe Eating, Y.-R.Chen, ed., Proc. SPIE 3544, 121-133 (1998).

Y. R. Chen, B. Park, R. W. Huffman, and M. Nguyen, "Classification of on-line poultry carcasses with backpropagation neural networks," J. Food Proc. Engr. 21(1), 33-48 (1998).

Y. R. Chen and D. R. Massie, "Visible/NIR reflectance and interactance spectroscopy for detection poultry carcasses," Trans. ASAE 36, 863-869 (1993).

Y. R. Chen and W. R. Hruschka, "On-line trials of a chicken carcass inspection system using visible/near-infrared reflectance," presented at the 1998 ASAE Annual International Meeting, Orlando, Fla., 12-15 July 1998, paper 983047.

Chen, Y.-R.

Y.-R. Chen, "Classifying diseased poultry carcasses by visible and near-IR reflectance spectroscopy," Optics in Agriculture and Forestry, J.A.Deshazer and G.E.Meyer, eds., Proc. SPIE 1836, 44-55 (1992).

Chia, A. S.

S. C. Liew, A. S. Chia, and L. K. Kwoh, "Evaluating the validity of SeaWifs chlorophyll algorithm for coastal waters," presented at the 22nd Asian Conference on Remote Sensing, Singapore, 5-9 November2001.

Clark, R. N.

R. F. Kokaly and R. N. Clark, "Spectroscopic determination of leaf biochemistry using band-depth analysis of absorption features and stepwise linear regression," Remote Sensing Environ. 67, 267-287 (1999).
[CrossRef]

R. N. Clark, A. J. Gallagher, and G. A. Swayze, "Material absorption band depth mapping of imaging spectrometer data using a complete band shape least-squares fit with library reference spectra," JPL Publ. 90-54, 176-186 (1990).

Dey, B. P.

B. P. Dey, Y. R. Chen, C. Hsieh, and D. E. Chan, "Detection of septicemia in chicken livers by spectroscopy," Poultry Sci. 82, 199-206 (2003).

Ding, F.

F. Ding, Y. R. Chen, K. Chao, and D. E. Chan, "Two-color mixing for classifying agricultural products for safety and quality," Appl. Opt. 45, 668-677 (2006).
[CrossRef]

F. Ding, Y. R. Chen, and K. Chao, "Application of color mixing for safety and quality inspection of agricultural products," in Optical Sensors and Sensing Systems for Natural Resources and Food Safety and Quality, Y.-R, Chen, G.E.Meyer, and S.-I.Tu, eds., Proc. SPIE5996, 59960R (2005).

F. Ding, Y. R. Chen, and K. Chao, "Two-waveband color-mixing binoculars for the detection of wholesome and unwholesome chicken carcasses: a simulation," Appl. Opt. 44, 5454-5462 (2005).
[CrossRef]

Fairchild, M. D.

M. D. Fairchild, "Revision of CIECAM97s for practical applications," Color Res. Appl. 26, 418-427 (2001).
[CrossRef]

Feind, R. E.

R. E. Feind and R. M. Welch, "Cloud fraction and cloud shadow property retrievals from coregistered TIMS and AVIRIS imagery: the use of cloud morphology for registration," IEEE Trans. Geosci. Remote Sens. 33, 172-184 (1995).
[CrossRef]

Gallagher, A. J.

R. N. Clark, A. J. Gallagher, and G. A. Swayze, "Material absorption band depth mapping of imaging spectrometer data using a complete band shape least-squares fit with library reference spectra," JPL Publ. 90-54, 176-186 (1990).

Gao, B. C.

B. C. Gao and A. F. Goetz, "Extraction of dry leaf spectral features from reflectance spectra of green vegetation," Remote Sens. Environ. 47, 369-274 (1994).
[CrossRef]

Ge, S.

R. Pu, S. Ge, N. M. Kelly, and P. Gong, "Spectral absorption features as indicators of water status in coast live oak (Quercus agrifolia) leaves, Intl. J. Remote Sens. 24, 1799-1810 (2003).
[CrossRef]

Goetz, A. F.

B. C. Gao and A. F. Goetz, "Extraction of dry leaf spectral features from reflectance spectra of green vegetation," Remote Sens. Environ. 47, 369-274 (1994).
[CrossRef]

Gong, P.

R. Pu, S. Ge, N. M. Kelly, and P. Gong, "Spectral absorption features as indicators of water status in coast live oak (Quercus agrifolia) leaves, Intl. J. Remote Sens. 24, 1799-1810 (2003).
[CrossRef]

Gwozdz, F. B.

K. Chao, Y. R. Chen, W. R. Hruschka, and F. B. Gwozdz, "On-line inspection of poultry carcasses by dual-camera system," J. Food Engr. 51 (3), 185-192 (2002).
[CrossRef]

Hruschka, W. R.

K. Chao, Y. R. Chen, W. R. Hruschka, and F. B. Gwozdz, "On-line inspection of poultry carcasses by dual-camera system," J. Food Engr. 51 (3), 185-192 (2002).
[CrossRef]

Y. R. Chen and W. R. Hruschka, "On-line trials of a chicken carcass inspection system using visible/near-infrared reflectance," presented at the 1998 ASAE Annual International Meeting, Orlando, Fla., 12-15 July 1998, paper 983047.

Hsieh, C.

B. P. Dey, Y. R. Chen, C. Hsieh, and D. E. Chan, "Detection of septicemia in chicken livers by spectroscopy," Poultry Sci. 82, 199-206 (2003).

Huffman, R. W.

Y. R. Chen, B. Park, R. W. Huffman, and M. Nguyen, "Classification of on-line poultry carcasses with backpropagation neural networks," J. Food Proc. Engr. 21(1), 33-48 (1998).

Hunt, R. W. G.

C. J. Li, M. R. Luo, and R. W. G. Hunt, "A revision of CIECAM97s model," Color Res. Appl. 25, 260-266 (2000).
[CrossRef]

Kelly, N. M.

R. Pu, S. Ge, N. M. Kelly, and P. Gong, "Spectral absorption features as indicators of water status in coast live oak (Quercus agrifolia) leaves, Intl. J. Remote Sens. 24, 1799-1810 (2003).
[CrossRef]

Kim, M. S.

P. M. Mehl, Y. R. Chen, M. S. Kim, and D. E. Chan "Development of hyperspectral imaging technique for the detection of apple surface detects and contaminations," J. Food Engr. 61, 67-81 (2004).
[CrossRef]

A. M. Lefcourt, M. S. Kim, and Y. R. Chen, "Automated detection of fecal contamination of apples by multispectral laser-induced fluorescence imaging," Appl. Opt. 42, 3935-3943 (2003).

M. S. Kim, A. M. Lefcourt, and Y. R. Chen, "Multispectral laser-induced fluorescence imaging system for large biological samples," Appl. Opt. 42, 3927-3934 (2003).

Y. R. Chen, K. Chao, and M. S. Kim, "Machine vision technology for agricultural applications," Comput. Electron. Agric. 36 (2), 173-191 (2002).
[CrossRef]

Kokaly, R. F.

R. F. Kokaly and R. N. Clark, "Spectroscopic determination of leaf biochemistry using band-depth analysis of absorption features and stepwise linear regression," Remote Sensing Environ. 67, 267-287 (1999).
[CrossRef]

Kwoh, L. K.

S. C. Liew, A. S. Chia, and L. K. Kwoh, "Evaluating the validity of SeaWifs chlorophyll algorithm for coastal waters," presented at the 22nd Asian Conference on Remote Sensing, Singapore, 5-9 November2001.

Lefcourt, A. M.

Li, C. J.

C. J. Li, M. R. Luo, and R. W. G. Hunt, "A revision of CIECAM97s model," Color Res. Appl. 25, 260-266 (2000).
[CrossRef]

Liew, S. C.

S. C. Liew, A. S. Chia, and L. K. Kwoh, "Evaluating the validity of SeaWifs chlorophyll algorithm for coastal waters," presented at the 22nd Asian Conference on Remote Sensing, Singapore, 5-9 November2001.

Lu, R.

R. Lu and Y. R. Chen, "Hyperspectral imaging for safety inspection of food and agricultural products," in Pathogen Detection and Remediation for Safe Eating, Y.-R.Chen, ed., Proc. SPIE 3544, 121-133 (1998).

Luo, M. R.

C. J. Li, M. R. Luo, and R. W. G. Hunt, "A revision of CIECAM97s model," Color Res. Appl. 25, 260-266 (2000).
[CrossRef]

Massie, D. R.

Y. R. Chen and D. R. Massie, "Visible/NIR reflectance and interactance spectroscopy for detection poultry carcasses," Trans. ASAE 36, 863-869 (1993).

Mehl, P. M.

P. M. Mehl, Y. R. Chen, M. S. Kim, and D. E. Chan "Development of hyperspectral imaging technique for the detection of apple surface detects and contaminations," J. Food Engr. 61, 67-81 (2004).
[CrossRef]

Nguyen, M.

Y. R. Chen, B. Park, R. W. Huffman, and M. Nguyen, "Classification of on-line poultry carcasses with backpropagation neural networks," J. Food Proc. Engr. 21(1), 33-48 (1998).

Park, B.

Y. R. Chen, B. Park, R. W. Huffman, and M. Nguyen, "Classification of on-line poultry carcasses with backpropagation neural networks," J. Food Proc. Engr. 21(1), 33-48 (1998).

Pu, R.

R. Pu, S. Ge, N. M. Kelly, and P. Gong, "Spectral absorption features as indicators of water status in coast live oak (Quercus agrifolia) leaves, Intl. J. Remote Sens. 24, 1799-1810 (2003).
[CrossRef]

Stiles, W. S.

G. Wyszecki and W. S. Stiles, Color Science: Concepts and Methods, Quantitative Data and Formulas (Wiley, 1982).

Swayze, G. A.

R. N. Clark, A. J. Gallagher, and G. A. Swayze, "Material absorption band depth mapping of imaging spectrometer data using a complete band shape least-squares fit with library reference spectra," JPL Publ. 90-54, 176-186 (1990).

Vriesenga, M.

M. Vriesenga, "Colored illumination for enhancing discriminability in machine vision," J. Visual Commun. Image Represent.6(3), 244-255 (1995).

Welch, R. M.

R. E. Feind and R. M. Welch, "Cloud fraction and cloud shadow property retrievals from coregistered TIMS and AVIRIS imagery: the use of cloud morphology for registration," IEEE Trans. Geosci. Remote Sens. 33, 172-184 (1995).
[CrossRef]

Wyszecki, G.

G. Wyszecki and W. S. Stiles, Color Science: Concepts and Methods, Quantitative Data and Formulas (Wiley, 1982).

Appl. Opt. (4)

Color Res. Appl. (2)

C. J. Li, M. R. Luo, and R. W. G. Hunt, "A revision of CIECAM97s model," Color Res. Appl. 25, 260-266 (2000).
[CrossRef]

M. D. Fairchild, "Revision of CIECAM97s for practical applications," Color Res. Appl. 26, 418-427 (2001).
[CrossRef]

Comput. Electron. Agric. (1)

Y. R. Chen, K. Chao, and M. S. Kim, "Machine vision technology for agricultural applications," Comput. Electron. Agric. 36 (2), 173-191 (2002).
[CrossRef]

IEEE Trans. Geosci. Remote Sens. (1)

R. E. Feind and R. M. Welch, "Cloud fraction and cloud shadow property retrievals from coregistered TIMS and AVIRIS imagery: the use of cloud morphology for registration," IEEE Trans. Geosci. Remote Sens. 33, 172-184 (1995).
[CrossRef]

Intl. J. Remote Sens. (1)

R. Pu, S. Ge, N. M. Kelly, and P. Gong, "Spectral absorption features as indicators of water status in coast live oak (Quercus agrifolia) leaves, Intl. J. Remote Sens. 24, 1799-1810 (2003).
[CrossRef]

J. Food Engr. (2)

P. M. Mehl, Y. R. Chen, M. S. Kim, and D. E. Chan "Development of hyperspectral imaging technique for the detection of apple surface detects and contaminations," J. Food Engr. 61, 67-81 (2004).
[CrossRef]

K. Chao, Y. R. Chen, W. R. Hruschka, and F. B. Gwozdz, "On-line inspection of poultry carcasses by dual-camera system," J. Food Engr. 51 (3), 185-192 (2002).
[CrossRef]

J. Food Proc. Engr. (1)

Y. R. Chen, B. Park, R. W. Huffman, and M. Nguyen, "Classification of on-line poultry carcasses with backpropagation neural networks," J. Food Proc. Engr. 21(1), 33-48 (1998).

JPL Publ. (1)

R. N. Clark, A. J. Gallagher, and G. A. Swayze, "Material absorption band depth mapping of imaging spectrometer data using a complete band shape least-squares fit with library reference spectra," JPL Publ. 90-54, 176-186 (1990).

Poultry Sci. (1)

B. P. Dey, Y. R. Chen, C. Hsieh, and D. E. Chan, "Detection of septicemia in chicken livers by spectroscopy," Poultry Sci. 82, 199-206 (2003).

Remote Sens. Environ. (1)

B. C. Gao and A. F. Goetz, "Extraction of dry leaf spectral features from reflectance spectra of green vegetation," Remote Sens. Environ. 47, 369-274 (1994).
[CrossRef]

Remote Sensing Environ. (1)

R. F. Kokaly and R. N. Clark, "Spectroscopic determination of leaf biochemistry using band-depth analysis of absorption features and stepwise linear regression," Remote Sensing Environ. 67, 267-287 (1999).
[CrossRef]

Trans. ASAE (1)

Y. R. Chen and D. R. Massie, "Visible/NIR reflectance and interactance spectroscopy for detection poultry carcasses," Trans. ASAE 36, 863-869 (1993).

Other (8)

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Y. R. Chen and W. R. Hruschka, "On-line trials of a chicken carcass inspection system using visible/near-infrared reflectance," presented at the 1998 ASAE Annual International Meeting, Orlando, Fla., 12-15 July 1998, paper 983047.

F. Ding, Y. R. Chen, and K. Chao, "Application of color mixing for safety and quality inspection of agricultural products," in Optical Sensors and Sensing Systems for Natural Resources and Food Safety and Quality, Y.-R, Chen, G.E.Meyer, and S.-I.Tu, eds., Proc. SPIE5996, 59960R (2005).

M. Vriesenga, "Colored illumination for enhancing discriminability in machine vision," J. Visual Commun. Image Represent.6(3), 244-255 (1995).

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S. C. Liew, A. S. Chia, and L. K. Kwoh, "Evaluating the validity of SeaWifs chlorophyll algorithm for coastal waters," presented at the 22nd Asian Conference on Remote Sensing, Singapore, 5-9 November2001.

R. Lu and Y. R. Chen, "Hyperspectral imaging for safety inspection of food and agricultural products," in Pathogen Detection and Remediation for Safe Eating, Y.-R.Chen, ed., Proc. SPIE 3544, 121-133 (1998).

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Figures (10)

Fig. 1
Fig. 1

Schematic of implementation of three-band ratio criterion (a) with multispectral imaging system; (b) with three-color mixing visual device.

Fig. 2
Fig. 2

(Color online) Schematic of binocular-based three-color mixing visual device.

Fig. 3
Fig. 3

Spectral transmission of the three-band filter.

Fig. 4
Fig. 4

Relative reflectance of chicken skin.

Fig. 5
Fig. 5

Flow chart of the algorithm for the selection of the optimal three wavebands.

Fig. 6
Fig. 6

Simulated color picture of one group of Gala apples in the wavelength range from 425 nm through 675 nm.

Fig. 7
Fig. 7

Relative reflectance of contaminations on Gala apples: (a) good skin at top-left apple; (b) good skin at top-right apple; (c) 1:20 diluted fecal contamination on top-left apple; (d) 1:20 diluted fecal contamination on top-right apple; (e) good skin at bottom-left apple; (f) 1:20 diluted fecal contamination on bottom-left apple; (g) good skin at bottom-right apple; (h) 1:2 diluted fecal contamination on bottom-left apple; (i) 1:20 diluted fecal contamination on bottom-right apple; (j) soil contamination on bottom-right apple.

Fig. 8
Fig. 8

Training color charts of Gala apples: (a) good skin at top-left apple; (b) good skin at top-right apple; (e) good skin at bottom-left apple; (g) good skin at bottom-right apple.

Fig. 9
Fig. 9

Simulated picture of the group of Gala apples at wavelength set 428 nm, 524 nm, and 641 nm.

Fig. 10
Fig. 10

Simulated picture of the group of Gala apples at wavelength set 461 nm, 630 nm, and 659 nm.

Tables (6)

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Table 1 Visual Device Optimal Wavelength of Three Bands

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Table 2 Multitarget Color Differences Comparison

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Table 3 Parameters at Wavelength Set 447 nm, 522 nm, and 627 nm

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Table 4 Saturation, Hue Angle, and Band Ratio at Wavelength Set 447, 522, and 627 nm

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Table 5 Color Differences between Gala Normal Skin and Contaminated Skins at Wavelength Set 428 nm, 524 nm, and 641 nm

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Table 6 Color Differences between Gala Normal Skin and Contaminated Skins at Wavelength Set 461 nm, 630 nm, and 659 nm

Equations (53)

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X = k λ τ λ ρ λ H λ x ¯ λ Δ λ ,
Y = k λ τ λ ρ λ H λ y ¯ λ Δ λ ,
Z = k λ τ λ ρ λ H λ z ¯ λ Δ λ ,
x m = ( k 12 x 1 + x 2 + k 32 x 3 ) / ( k 12 + k 32 + 1 ) ,
y m = ( k 12 y 1 + y 2 + k 32 y 3 ) / ( k 12 + k 32 + 1 ) ,
k i 2 = ( X i + Y i + Z i ) / ( X 2 + Y 2 + Z 2 ) ( i = 1 , 3 ) .
C 3 br = E λ 1 : E λ 2 : E λ 3 ,
E λ i = λ i Δ λ i / 2 λ i + Δ λ i / 2 F ( x s , y s , z s ) τ λ ρ λ H λ S λ d λ
( i = 1 , 2 , 3 ) ,
C 3 br = λ 1 Δ λ 1 / 2 λ 1 + Δ λ 1 / 2 τ λ ρ λ H λ S λ d λ : λ 2 Δ λ 2 / 2 λ 2 + Δ λ 2 / 2 τ ρ λ H λ S λ d λ : λ 3 Δ λ 3 / 2 λ 3 + Δ λ 3 / 2 τ λ ρ λ H λ S λ d λ .
C 3 br = τ λ 1 ρ λ 1 H λ 1 S λ 1 Δ λ 1 : τ λ 2 ρ λ 2 H λ 2 S λ 2 Δ λ 2 : τ λ 3 ρ λ 3 H λ 3 S λ 3 Δ λ 3 ,
C 3 br = C 12 : 1 : C 32 ,
C 12 = τ λ 1 ρ λ 1 H λ 1 S λ 1 Δ λ 1 τ λ 2 ρ λ 2 H λ 2 S λ 2 Δ λ 2 ,
C 32 = τ λ 3 ρ λ 3 H λ 3 S λ 3 Δ λ 3 τ λ 2 ρ λ 2 H λ 2 S λ 2 Δ λ 2 .
k 1 = 2 λ 2 λ 1 λ 3 λ 1 , k 2 = 2 λ 3 λ 2 λ 3 λ 1 .
k i 2 = τ λ 1 τ λ 2 H λ 1 H λ 2 S λ 2 ( x ¯ λ i + y ¯ λ i + z ¯ λ i ) τ λ 2 τ λ 1 H λ 2 H λ 1 S λ 1 ( x ¯ λ 2 + y ¯ λ 2 + z ¯ λ 2 ) C i 2 ( i = 1 , 3 ) ,
k i 2 = c i C i 2 ( i = 1 , 3 ) .
s u v * = 13 [ ( u u n ) 2 + ( v v n ) 2 ] 1 / 2 ,
h u v = arctan ( v / u ) .
s u v * = [ ( a 1 + a 2 C 12 + a 3 C 32 a 4 + a 5 C 12 + a 6 C 32 ) 2 + ( a 7 + a 8 C 12 + a 9 C 32 a 4 + a 5 C 12 + a 6 C 32 ) 2 ] 1 / 2 ,
h u v = arctan [ ( a 1 + a 2 C 12 + a 3 C 32 ) / ( a 7 + a 8 C 12 + a 9 C 32 ) ] ,
C 32 = d 1 + d 2 cos ( h u v ) s u v * + d 3 sin ( h u v ) s u v * d 4 + d 5 cos ( h u v ) s u v * + d 6 sin ( h u v ) s u v * ,
C 12 = d 7 cos ( h u v ) + d 8 sin ( h u v ) + s u v * [ d 9 cos ( 2 h u v ) + d 10 sin ( 2 h u v ) + d 11 ] d 12 cos ( h u v ) + d 13 sin ( h u v ) + s u v * [ d 14 cos ( 2 h u v ) + d 15 sin ( 2 h u v ) + d 16 ] ,
Δ E ( L * u * v * ) = [ ( Δ L * ) 2 + ( Δ u * ) 2 + ( Δ v * ) 2 ] 1 / 2 ,
Δ S = 13 [ ( Δ u ) 2 + ( Δ v ) 2 ] 0.5 .
R t λ = A total A tumor × R o λ ( A total A tumor 1 ) × R n λ ,
a 1 = 9 y 2 w 0 ( x 2 + 15 y 2 + 3 z 2 ) ,
a 2 = 9 y 1 w 0 ( x 1 + 15 y 1 + 3 z 1 ) ,
a 3 = 9 y 3 w 0 ( x 3 + 15 y 3 + 3 z 3 ) ,
a 4 = 4 x 2 w 1 ( x 2 + 15 y 2 + 3 z 2 ) ,
a 5 = 4 x 1 w 1 ( x 1 + 15 y 1 + 3 z 1 ) ,
a 6 = 4 x 3 w 1 ( x 3 + 15 y 3 + 3 z 3 ) ,
a 7 = x 2 + 15 y 2 + 3 z 2 ,
a 8 = x 1 + 15 y 1 + 3 z 1 ,
a 9 = x 3 + 15 y 3 + 3 z 3 ,
w 0 = 9 y n / ( x n + 15 y n + 3 z n ) ,
w 1 = 4 x n / ( x n + 15 y n + 3 z n ) ,
d 1 = a 2 a 4 a 1 a 5 ,
d 2 = ( a 1 a 8 a 2 a 7 ) / 13 ,
d 3 = ( a 5 a 7 a 4 a 8 ) / 13 ,
d 4 = a 3 a 5 a 2 a 6 ,
d 5 = ( a 2 a 9 a 3 a 8 ) / 13 ,
d 6 = ( a 6 a 8 a 5 a 9 ) / 13 ,
d 7 = a 2 a 3 a 4 a 1 a 2 a 6 ,
d 8 = a 1 a 5 a 6 a 3 a 4 a 5 ,
d 9 = ( a 1 a 2 a 9 a 2 a 3 a 7 + a 5 a 6 a 7 a 4 a 5 a 9 ) / 26 ,
d 10 = ( a 3 a 5 a 7 + a 2 a 6 a 7 a 1 a 5 a 9 a 2 a 4 a 9 ) / 26 ,
d 11 = ( a 1 a 2 a 9 a 2 a 3 a 7 + a 4 a 5 a 9 a 5 a 6 a 7 ) / 26 ,
d 12 = ( a 2 ) 2 a 6 a 2 a 3 a 5 ,
d 13 = a 3 ( a 5 ) 2 a 2 a 5 a 6 ,
d 14 = ( a 2 a 3 a 8 ( a 2 ) 2 a 9 + ( a 5 ) 2 a 9 a 5 a 6 a 8 ) / 26 ,
d 15 = ( 2 a 2 a 5 a 9 a 2 a 6 a 8 a 3 a 5 a 8 ) / 26 ,
d 16 = ( a 2 a 3 a 8 ( a 2 ) 2 a 9 + a 5 a 6 a 8 ( a 5 ) 2 a 9 ) / 26 .

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