Abstract

We consider a feature selection method to detect skin tumors on chicken carcasses using hyperspectral (HS) reflectance data. Detection of chicken tumors is difficult because the tumors vary in size and shape; some tumors are small, early-stage tumor spots. We make use of the fact that a chicken skin tumor consists of a lesion region surrounded by a region of thickened skin and that the spectral responses of the lesion and the thickened-skin regions of tumors are considerably different and train our feature selection algorithm to separately detect lesion regions and thickened-skin regions; we then fuse the two HS detection results to reduce false alarms. To the best of our knowledge, these techniques are new. Our forward selection and modified branch and bound algorithm is used to select a small number of λ spectral features that are useful for discrimination. Initial results show that our method offers promise for a good tumor detection rate and a low false alarm rate.

© 2007 Optical Society of America

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  1. B. Thai and G. Healey, "Invariant subpixel target identification in hyperspectral imagery," in Proc. SPIE 3717, 14-24 (1999).
    [CrossRef]
  2. D. Casasent and X.-W. Chen, "Feature reduction and morphological processing for hyperspectral image data," Appl. Opt. 43, 227-236 (2004).
    [CrossRef] [PubMed]
  3. J. Goutsias and A. Banerji, "A morphological approach to automatic mine detection problems," IEEE Trans. Aerosp. Electron. Syst. 34, 1085-1096 (1998).
    [CrossRef]
  4. M. J. Muasher and D. A. Landgrebe, "The K-L expansion as an effective feature ordering techniques for limited training sample size," IEEE Trans. Geosci. Remote Sens. GE-21, 438-441 (1983).
    [CrossRef]
  5. T. Pearson, "Spectral properties and effect of drying temperature on almonds with conceal damage," Lebensm.-Wiss. Technol. 32, 67-72 (1999).
    [CrossRef]
  6. F. Dowell, M. Ram, and L. Seitz, "Predicting scab, vomitoxin, and ergosterol in single wheat kernels using near-infrared spectroscopy," Cereal Chem. 76, 573-576 (1999).
    [CrossRef]
  7. T. C. Pearson, D. T. Wicklow, E. B. Maghirang, F. Xie, and F. E. Dowell, "Detecting aflatoxin in single corn kernels by transmittance and reflectance spectroscopy," Trans. ASAE 44, 1247-1254 (2001).
  8. F. Dowell, T. Pearson, E. Maghirang, F. Xie, and D. Wicklow, "Reflectance and transmittance spectroscopy applied to detecting fumonisin in single corn kernels infected with Fusarium verticillioides," Cereal Chem. 79, 222-226 (2002).
    [CrossRef]
  9. B. Park, K. C. Lawrence, W. R. Windham, and R. J. Buhr, "Hyperspectral imaging for detecting fecal and ingesta contaminants on poultry carcasses," Trans. ASAE 45, 2017-2026 (2002).
  10. K. Chao, P. M. Mehl, and Y. R. Chen, "Use of hyper- and multi-spectral imaging for detection of chicken skin tumors," Appl. Eng. Agric. 18, 113-119 (2002).
  11. W. R. Windham, K. C. Lawrence, B. Park, and R. J. Buhr, "Visible/NIR spectroscopy for characterizing fecal contamination of chicken carcasses," Trans. ASAE 46, 747-751 (2003).
  12. D. Casasent and X.-W. Chen, "Waveband selection for hyperspectral data: optimal feature selection," in Proc. SPIE 5106, 259-270 (2003).
    [CrossRef]
  13. I. Kim, M. Kim, Y.-R. Chen, and S. Kong, "Detection of skin tumors on chicken carcasses using hyperspectral fluorescence imaging," Trans. ASAE 47, 1785-1792 (2004).
  14. S. Kong, Y.-R. Chen, I. Kim, and M. Kim, "Analysis of hyperspectral fluorescence images for poultry skin tumor inspection," Appl. Opt. 43, 824-833 (2004).
    [CrossRef] [PubMed]
  15. A. Jain, R. Ruin, and J. Mao, "Statistical pattern recognition: a review," IEEE Trans. Pattern Anal. Mach. Intell. 22, 4-37 (2000).
    [CrossRef]
  16. M. S. Kim, Y. R. Chen, and P. M. Mehl, "Hyperspectral reflectance and fluorescence imaging system for food quality and safety," Trans. ASAE 44, 721-729 (2001).
  17. B. W. Calnek, H. John Barnes, C. W. Beard, W. M. Reid, and H. W. Yoder, Diseases of Poultry, 9th ed. (Iowa State U., 1991), Chap. 16, pp. 386-484.
  18. P. Narendra and K. Fukunaga, "A branch and bound algorithm for feature subset selection," IEEE Trans. Comput. 26, 917-922 (1977).
    [CrossRef]
  19. K. Fukunaga, Introduction to Statistical Pattern Recognition, 2nd ed. (Academic, 1992).
  20. G. Furnival and R. Wilson, "Regression by leaps and bounds," Technometrics 16, 499-511 (1974).
    [CrossRef]
  21. D. Ballard and C. Brown, Computer Vision (Prentice-Hall, 1982), p. 151.
  22. J. Vila, J. Calpe, F. Pla, L. Gomes, J. Connell, J. Marchant, J. Calleja, M. Mulqueen, J. Munoz, and A. Klaren, "SmartSpectra: applying multispectral imaging to industrial environments," Real-Time Imag. 11, 85-98 (2005).
    [CrossRef]

2005

J. Vila, J. Calpe, F. Pla, L. Gomes, J. Connell, J. Marchant, J. Calleja, M. Mulqueen, J. Munoz, and A. Klaren, "SmartSpectra: applying multispectral imaging to industrial environments," Real-Time Imag. 11, 85-98 (2005).
[CrossRef]

2004

2003

W. R. Windham, K. C. Lawrence, B. Park, and R. J. Buhr, "Visible/NIR spectroscopy for characterizing fecal contamination of chicken carcasses," Trans. ASAE 46, 747-751 (2003).

D. Casasent and X.-W. Chen, "Waveband selection for hyperspectral data: optimal feature selection," in Proc. SPIE 5106, 259-270 (2003).
[CrossRef]

2002

F. Dowell, T. Pearson, E. Maghirang, F. Xie, and D. Wicklow, "Reflectance and transmittance spectroscopy applied to detecting fumonisin in single corn kernels infected with Fusarium verticillioides," Cereal Chem. 79, 222-226 (2002).
[CrossRef]

B. Park, K. C. Lawrence, W. R. Windham, and R. J. Buhr, "Hyperspectral imaging for detecting fecal and ingesta contaminants on poultry carcasses," Trans. ASAE 45, 2017-2026 (2002).

K. Chao, P. M. Mehl, and Y. R. Chen, "Use of hyper- and multi-spectral imaging for detection of chicken skin tumors," Appl. Eng. Agric. 18, 113-119 (2002).

2001

M. S. Kim, Y. R. Chen, and P. M. Mehl, "Hyperspectral reflectance and fluorescence imaging system for food quality and safety," Trans. ASAE 44, 721-729 (2001).

T. C. Pearson, D. T. Wicklow, E. B. Maghirang, F. Xie, and F. E. Dowell, "Detecting aflatoxin in single corn kernels by transmittance and reflectance spectroscopy," Trans. ASAE 44, 1247-1254 (2001).

2000

A. Jain, R. Ruin, and J. Mao, "Statistical pattern recognition: a review," IEEE Trans. Pattern Anal. Mach. Intell. 22, 4-37 (2000).
[CrossRef]

1999

B. Thai and G. Healey, "Invariant subpixel target identification in hyperspectral imagery," in Proc. SPIE 3717, 14-24 (1999).
[CrossRef]

T. Pearson, "Spectral properties and effect of drying temperature on almonds with conceal damage," Lebensm.-Wiss. Technol. 32, 67-72 (1999).
[CrossRef]

F. Dowell, M. Ram, and L. Seitz, "Predicting scab, vomitoxin, and ergosterol in single wheat kernels using near-infrared spectroscopy," Cereal Chem. 76, 573-576 (1999).
[CrossRef]

1998

J. Goutsias and A. Banerji, "A morphological approach to automatic mine detection problems," IEEE Trans. Aerosp. Electron. Syst. 34, 1085-1096 (1998).
[CrossRef]

1983

M. J. Muasher and D. A. Landgrebe, "The K-L expansion as an effective feature ordering techniques for limited training sample size," IEEE Trans. Geosci. Remote Sens. GE-21, 438-441 (1983).
[CrossRef]

1977

P. Narendra and K. Fukunaga, "A branch and bound algorithm for feature subset selection," IEEE Trans. Comput. 26, 917-922 (1977).
[CrossRef]

1974

G. Furnival and R. Wilson, "Regression by leaps and bounds," Technometrics 16, 499-511 (1974).
[CrossRef]

Ballard, D.

D. Ballard and C. Brown, Computer Vision (Prentice-Hall, 1982), p. 151.

Banerji, A.

J. Goutsias and A. Banerji, "A morphological approach to automatic mine detection problems," IEEE Trans. Aerosp. Electron. Syst. 34, 1085-1096 (1998).
[CrossRef]

Barnes, H. John

B. W. Calnek, H. John Barnes, C. W. Beard, W. M. Reid, and H. W. Yoder, Diseases of Poultry, 9th ed. (Iowa State U., 1991), Chap. 16, pp. 386-484.

Beard, C. W.

B. W. Calnek, H. John Barnes, C. W. Beard, W. M. Reid, and H. W. Yoder, Diseases of Poultry, 9th ed. (Iowa State U., 1991), Chap. 16, pp. 386-484.

Brown, C.

D. Ballard and C. Brown, Computer Vision (Prentice-Hall, 1982), p. 151.

Buhr, R. J.

W. R. Windham, K. C. Lawrence, B. Park, and R. J. Buhr, "Visible/NIR spectroscopy for characterizing fecal contamination of chicken carcasses," Trans. ASAE 46, 747-751 (2003).

B. Park, K. C. Lawrence, W. R. Windham, and R. J. Buhr, "Hyperspectral imaging for detecting fecal and ingesta contaminants on poultry carcasses," Trans. ASAE 45, 2017-2026 (2002).

Calleja, J.

J. Vila, J. Calpe, F. Pla, L. Gomes, J. Connell, J. Marchant, J. Calleja, M. Mulqueen, J. Munoz, and A. Klaren, "SmartSpectra: applying multispectral imaging to industrial environments," Real-Time Imag. 11, 85-98 (2005).
[CrossRef]

Calnek, B. W.

B. W. Calnek, H. John Barnes, C. W. Beard, W. M. Reid, and H. W. Yoder, Diseases of Poultry, 9th ed. (Iowa State U., 1991), Chap. 16, pp. 386-484.

Calpe, J.

J. Vila, J. Calpe, F. Pla, L. Gomes, J. Connell, J. Marchant, J. Calleja, M. Mulqueen, J. Munoz, and A. Klaren, "SmartSpectra: applying multispectral imaging to industrial environments," Real-Time Imag. 11, 85-98 (2005).
[CrossRef]

Casasent, D.

D. Casasent and X.-W. Chen, "Feature reduction and morphological processing for hyperspectral image data," Appl. Opt. 43, 227-236 (2004).
[CrossRef] [PubMed]

D. Casasent and X.-W. Chen, "Waveband selection for hyperspectral data: optimal feature selection," in Proc. SPIE 5106, 259-270 (2003).
[CrossRef]

Chao, K.

K. Chao, P. M. Mehl, and Y. R. Chen, "Use of hyper- and multi-spectral imaging for detection of chicken skin tumors," Appl. Eng. Agric. 18, 113-119 (2002).

Chen, X.-W.

D. Casasent and X.-W. Chen, "Feature reduction and morphological processing for hyperspectral image data," Appl. Opt. 43, 227-236 (2004).
[CrossRef] [PubMed]

D. Casasent and X.-W. Chen, "Waveband selection for hyperspectral data: optimal feature selection," in Proc. SPIE 5106, 259-270 (2003).
[CrossRef]

Chen, Y. R.

K. Chao, P. M. Mehl, and Y. R. Chen, "Use of hyper- and multi-spectral imaging for detection of chicken skin tumors," Appl. Eng. Agric. 18, 113-119 (2002).

M. S. Kim, Y. R. Chen, and P. M. Mehl, "Hyperspectral reflectance and fluorescence imaging system for food quality and safety," Trans. ASAE 44, 721-729 (2001).

Chen, Y.-R.

I. Kim, M. Kim, Y.-R. Chen, and S. Kong, "Detection of skin tumors on chicken carcasses using hyperspectral fluorescence imaging," Trans. ASAE 47, 1785-1792 (2004).

S. Kong, Y.-R. Chen, I. Kim, and M. Kim, "Analysis of hyperspectral fluorescence images for poultry skin tumor inspection," Appl. Opt. 43, 824-833 (2004).
[CrossRef] [PubMed]

Connell, J.

J. Vila, J. Calpe, F. Pla, L. Gomes, J. Connell, J. Marchant, J. Calleja, M. Mulqueen, J. Munoz, and A. Klaren, "SmartSpectra: applying multispectral imaging to industrial environments," Real-Time Imag. 11, 85-98 (2005).
[CrossRef]

Dowell, F.

F. Dowell, T. Pearson, E. Maghirang, F. Xie, and D. Wicklow, "Reflectance and transmittance spectroscopy applied to detecting fumonisin in single corn kernels infected with Fusarium verticillioides," Cereal Chem. 79, 222-226 (2002).
[CrossRef]

F. Dowell, M. Ram, and L. Seitz, "Predicting scab, vomitoxin, and ergosterol in single wheat kernels using near-infrared spectroscopy," Cereal Chem. 76, 573-576 (1999).
[CrossRef]

Dowell, F. E.

T. C. Pearson, D. T. Wicklow, E. B. Maghirang, F. Xie, and F. E. Dowell, "Detecting aflatoxin in single corn kernels by transmittance and reflectance spectroscopy," Trans. ASAE 44, 1247-1254 (2001).

Fukunaga, K.

P. Narendra and K. Fukunaga, "A branch and bound algorithm for feature subset selection," IEEE Trans. Comput. 26, 917-922 (1977).
[CrossRef]

K. Fukunaga, Introduction to Statistical Pattern Recognition, 2nd ed. (Academic, 1992).

Furnival, G.

G. Furnival and R. Wilson, "Regression by leaps and bounds," Technometrics 16, 499-511 (1974).
[CrossRef]

Gomes, L.

J. Vila, J. Calpe, F. Pla, L. Gomes, J. Connell, J. Marchant, J. Calleja, M. Mulqueen, J. Munoz, and A. Klaren, "SmartSpectra: applying multispectral imaging to industrial environments," Real-Time Imag. 11, 85-98 (2005).
[CrossRef]

Goutsias, J.

J. Goutsias and A. Banerji, "A morphological approach to automatic mine detection problems," IEEE Trans. Aerosp. Electron. Syst. 34, 1085-1096 (1998).
[CrossRef]

Healey, G.

B. Thai and G. Healey, "Invariant subpixel target identification in hyperspectral imagery," in Proc. SPIE 3717, 14-24 (1999).
[CrossRef]

Jain, A.

A. Jain, R. Ruin, and J. Mao, "Statistical pattern recognition: a review," IEEE Trans. Pattern Anal. Mach. Intell. 22, 4-37 (2000).
[CrossRef]

Kim, I.

I. Kim, M. Kim, Y.-R. Chen, and S. Kong, "Detection of skin tumors on chicken carcasses using hyperspectral fluorescence imaging," Trans. ASAE 47, 1785-1792 (2004).

S. Kong, Y.-R. Chen, I. Kim, and M. Kim, "Analysis of hyperspectral fluorescence images for poultry skin tumor inspection," Appl. Opt. 43, 824-833 (2004).
[CrossRef] [PubMed]

Kim, M.

S. Kong, Y.-R. Chen, I. Kim, and M. Kim, "Analysis of hyperspectral fluorescence images for poultry skin tumor inspection," Appl. Opt. 43, 824-833 (2004).
[CrossRef] [PubMed]

I. Kim, M. Kim, Y.-R. Chen, and S. Kong, "Detection of skin tumors on chicken carcasses using hyperspectral fluorescence imaging," Trans. ASAE 47, 1785-1792 (2004).

Kim, M. S.

M. S. Kim, Y. R. Chen, and P. M. Mehl, "Hyperspectral reflectance and fluorescence imaging system for food quality and safety," Trans. ASAE 44, 721-729 (2001).

Klaren, A.

J. Vila, J. Calpe, F. Pla, L. Gomes, J. Connell, J. Marchant, J. Calleja, M. Mulqueen, J. Munoz, and A. Klaren, "SmartSpectra: applying multispectral imaging to industrial environments," Real-Time Imag. 11, 85-98 (2005).
[CrossRef]

Kong, S.

I. Kim, M. Kim, Y.-R. Chen, and S. Kong, "Detection of skin tumors on chicken carcasses using hyperspectral fluorescence imaging," Trans. ASAE 47, 1785-1792 (2004).

S. Kong, Y.-R. Chen, I. Kim, and M. Kim, "Analysis of hyperspectral fluorescence images for poultry skin tumor inspection," Appl. Opt. 43, 824-833 (2004).
[CrossRef] [PubMed]

Landgrebe, D. A.

M. J. Muasher and D. A. Landgrebe, "The K-L expansion as an effective feature ordering techniques for limited training sample size," IEEE Trans. Geosci. Remote Sens. GE-21, 438-441 (1983).
[CrossRef]

Lawrence, K. C.

W. R. Windham, K. C. Lawrence, B. Park, and R. J. Buhr, "Visible/NIR spectroscopy for characterizing fecal contamination of chicken carcasses," Trans. ASAE 46, 747-751 (2003).

B. Park, K. C. Lawrence, W. R. Windham, and R. J. Buhr, "Hyperspectral imaging for detecting fecal and ingesta contaminants on poultry carcasses," Trans. ASAE 45, 2017-2026 (2002).

Maghirang, E.

F. Dowell, T. Pearson, E. Maghirang, F. Xie, and D. Wicklow, "Reflectance and transmittance spectroscopy applied to detecting fumonisin in single corn kernels infected with Fusarium verticillioides," Cereal Chem. 79, 222-226 (2002).
[CrossRef]

Maghirang, E. B.

T. C. Pearson, D. T. Wicklow, E. B. Maghirang, F. Xie, and F. E. Dowell, "Detecting aflatoxin in single corn kernels by transmittance and reflectance spectroscopy," Trans. ASAE 44, 1247-1254 (2001).

Mao, J.

A. Jain, R. Ruin, and J. Mao, "Statistical pattern recognition: a review," IEEE Trans. Pattern Anal. Mach. Intell. 22, 4-37 (2000).
[CrossRef]

Marchant, J.

J. Vila, J. Calpe, F. Pla, L. Gomes, J. Connell, J. Marchant, J. Calleja, M. Mulqueen, J. Munoz, and A. Klaren, "SmartSpectra: applying multispectral imaging to industrial environments," Real-Time Imag. 11, 85-98 (2005).
[CrossRef]

Mehl, P. M.

K. Chao, P. M. Mehl, and Y. R. Chen, "Use of hyper- and multi-spectral imaging for detection of chicken skin tumors," Appl. Eng. Agric. 18, 113-119 (2002).

M. S. Kim, Y. R. Chen, and P. M. Mehl, "Hyperspectral reflectance and fluorescence imaging system for food quality and safety," Trans. ASAE 44, 721-729 (2001).

Muasher, M. J.

M. J. Muasher and D. A. Landgrebe, "The K-L expansion as an effective feature ordering techniques for limited training sample size," IEEE Trans. Geosci. Remote Sens. GE-21, 438-441 (1983).
[CrossRef]

Mulqueen, M.

J. Vila, J. Calpe, F. Pla, L. Gomes, J. Connell, J. Marchant, J. Calleja, M. Mulqueen, J. Munoz, and A. Klaren, "SmartSpectra: applying multispectral imaging to industrial environments," Real-Time Imag. 11, 85-98 (2005).
[CrossRef]

Munoz, J.

J. Vila, J. Calpe, F. Pla, L. Gomes, J. Connell, J. Marchant, J. Calleja, M. Mulqueen, J. Munoz, and A. Klaren, "SmartSpectra: applying multispectral imaging to industrial environments," Real-Time Imag. 11, 85-98 (2005).
[CrossRef]

Narendra, P.

P. Narendra and K. Fukunaga, "A branch and bound algorithm for feature subset selection," IEEE Trans. Comput. 26, 917-922 (1977).
[CrossRef]

Park, B.

W. R. Windham, K. C. Lawrence, B. Park, and R. J. Buhr, "Visible/NIR spectroscopy for characterizing fecal contamination of chicken carcasses," Trans. ASAE 46, 747-751 (2003).

B. Park, K. C. Lawrence, W. R. Windham, and R. J. Buhr, "Hyperspectral imaging for detecting fecal and ingesta contaminants on poultry carcasses," Trans. ASAE 45, 2017-2026 (2002).

Pearson, T.

F. Dowell, T. Pearson, E. Maghirang, F. Xie, and D. Wicklow, "Reflectance and transmittance spectroscopy applied to detecting fumonisin in single corn kernels infected with Fusarium verticillioides," Cereal Chem. 79, 222-226 (2002).
[CrossRef]

T. Pearson, "Spectral properties and effect of drying temperature on almonds with conceal damage," Lebensm.-Wiss. Technol. 32, 67-72 (1999).
[CrossRef]

Pearson, T. C.

T. C. Pearson, D. T. Wicklow, E. B. Maghirang, F. Xie, and F. E. Dowell, "Detecting aflatoxin in single corn kernels by transmittance and reflectance spectroscopy," Trans. ASAE 44, 1247-1254 (2001).

Pla, F.

J. Vila, J. Calpe, F. Pla, L. Gomes, J. Connell, J. Marchant, J. Calleja, M. Mulqueen, J. Munoz, and A. Klaren, "SmartSpectra: applying multispectral imaging to industrial environments," Real-Time Imag. 11, 85-98 (2005).
[CrossRef]

Ram, M.

F. Dowell, M. Ram, and L. Seitz, "Predicting scab, vomitoxin, and ergosterol in single wheat kernels using near-infrared spectroscopy," Cereal Chem. 76, 573-576 (1999).
[CrossRef]

Reid, W. M.

B. W. Calnek, H. John Barnes, C. W. Beard, W. M. Reid, and H. W. Yoder, Diseases of Poultry, 9th ed. (Iowa State U., 1991), Chap. 16, pp. 386-484.

Ruin, R.

A. Jain, R. Ruin, and J. Mao, "Statistical pattern recognition: a review," IEEE Trans. Pattern Anal. Mach. Intell. 22, 4-37 (2000).
[CrossRef]

Seitz, L.

F. Dowell, M. Ram, and L. Seitz, "Predicting scab, vomitoxin, and ergosterol in single wheat kernels using near-infrared spectroscopy," Cereal Chem. 76, 573-576 (1999).
[CrossRef]

Thai, B.

B. Thai and G. Healey, "Invariant subpixel target identification in hyperspectral imagery," in Proc. SPIE 3717, 14-24 (1999).
[CrossRef]

Vila, J.

J. Vila, J. Calpe, F. Pla, L. Gomes, J. Connell, J. Marchant, J. Calleja, M. Mulqueen, J. Munoz, and A. Klaren, "SmartSpectra: applying multispectral imaging to industrial environments," Real-Time Imag. 11, 85-98 (2005).
[CrossRef]

Wicklow, D.

F. Dowell, T. Pearson, E. Maghirang, F. Xie, and D. Wicklow, "Reflectance and transmittance spectroscopy applied to detecting fumonisin in single corn kernels infected with Fusarium verticillioides," Cereal Chem. 79, 222-226 (2002).
[CrossRef]

Wicklow, D. T.

T. C. Pearson, D. T. Wicklow, E. B. Maghirang, F. Xie, and F. E. Dowell, "Detecting aflatoxin in single corn kernels by transmittance and reflectance spectroscopy," Trans. ASAE 44, 1247-1254 (2001).

Wilson, R.

G. Furnival and R. Wilson, "Regression by leaps and bounds," Technometrics 16, 499-511 (1974).
[CrossRef]

Windham, W. R.

W. R. Windham, K. C. Lawrence, B. Park, and R. J. Buhr, "Visible/NIR spectroscopy for characterizing fecal contamination of chicken carcasses," Trans. ASAE 46, 747-751 (2003).

B. Park, K. C. Lawrence, W. R. Windham, and R. J. Buhr, "Hyperspectral imaging for detecting fecal and ingesta contaminants on poultry carcasses," Trans. ASAE 45, 2017-2026 (2002).

Xie, F.

F. Dowell, T. Pearson, E. Maghirang, F. Xie, and D. Wicklow, "Reflectance and transmittance spectroscopy applied to detecting fumonisin in single corn kernels infected with Fusarium verticillioides," Cereal Chem. 79, 222-226 (2002).
[CrossRef]

T. C. Pearson, D. T. Wicklow, E. B. Maghirang, F. Xie, and F. E. Dowell, "Detecting aflatoxin in single corn kernels by transmittance and reflectance spectroscopy," Trans. ASAE 44, 1247-1254 (2001).

Yoder, H. W.

B. W. Calnek, H. John Barnes, C. W. Beard, W. M. Reid, and H. W. Yoder, Diseases of Poultry, 9th ed. (Iowa State U., 1991), Chap. 16, pp. 386-484.

Appl. Eng. Agric.

K. Chao, P. M. Mehl, and Y. R. Chen, "Use of hyper- and multi-spectral imaging for detection of chicken skin tumors," Appl. Eng. Agric. 18, 113-119 (2002).

Appl. Opt.

Cereal Chem.

F. Dowell, T. Pearson, E. Maghirang, F. Xie, and D. Wicklow, "Reflectance and transmittance spectroscopy applied to detecting fumonisin in single corn kernels infected with Fusarium verticillioides," Cereal Chem. 79, 222-226 (2002).
[CrossRef]

F. Dowell, M. Ram, and L. Seitz, "Predicting scab, vomitoxin, and ergosterol in single wheat kernels using near-infrared spectroscopy," Cereal Chem. 76, 573-576 (1999).
[CrossRef]

IEEE Trans. Aerosp. Electron. Syst.

J. Goutsias and A. Banerji, "A morphological approach to automatic mine detection problems," IEEE Trans. Aerosp. Electron. Syst. 34, 1085-1096 (1998).
[CrossRef]

IEEE Trans. Comput.

P. Narendra and K. Fukunaga, "A branch and bound algorithm for feature subset selection," IEEE Trans. Comput. 26, 917-922 (1977).
[CrossRef]

IEEE Trans. Geosci. Remote Sens.

M. J. Muasher and D. A. Landgrebe, "The K-L expansion as an effective feature ordering techniques for limited training sample size," IEEE Trans. Geosci. Remote Sens. GE-21, 438-441 (1983).
[CrossRef]

IEEE Trans. Pattern Anal. Mach. Intell.

A. Jain, R. Ruin, and J. Mao, "Statistical pattern recognition: a review," IEEE Trans. Pattern Anal. Mach. Intell. 22, 4-37 (2000).
[CrossRef]

Lebensm.-Wiss. Technol.

T. Pearson, "Spectral properties and effect of drying temperature on almonds with conceal damage," Lebensm.-Wiss. Technol. 32, 67-72 (1999).
[CrossRef]

Proc. SPIE

D. Casasent and X.-W. Chen, "Waveband selection for hyperspectral data: optimal feature selection," in Proc. SPIE 5106, 259-270 (2003).
[CrossRef]

B. Thai and G. Healey, "Invariant subpixel target identification in hyperspectral imagery," in Proc. SPIE 3717, 14-24 (1999).
[CrossRef]

Real-Time Imag.

J. Vila, J. Calpe, F. Pla, L. Gomes, J. Connell, J. Marchant, J. Calleja, M. Mulqueen, J. Munoz, and A. Klaren, "SmartSpectra: applying multispectral imaging to industrial environments," Real-Time Imag. 11, 85-98 (2005).
[CrossRef]

Technometrics

G. Furnival and R. Wilson, "Regression by leaps and bounds," Technometrics 16, 499-511 (1974).
[CrossRef]

Trans. ASAE

I. Kim, M. Kim, Y.-R. Chen, and S. Kong, "Detection of skin tumors on chicken carcasses using hyperspectral fluorescence imaging," Trans. ASAE 47, 1785-1792 (2004).

M. S. Kim, Y. R. Chen, and P. M. Mehl, "Hyperspectral reflectance and fluorescence imaging system for food quality and safety," Trans. ASAE 44, 721-729 (2001).

T. C. Pearson, D. T. Wicklow, E. B. Maghirang, F. Xie, and F. E. Dowell, "Detecting aflatoxin in single corn kernels by transmittance and reflectance spectroscopy," Trans. ASAE 44, 1247-1254 (2001).

B. Park, K. C. Lawrence, W. R. Windham, and R. J. Buhr, "Hyperspectral imaging for detecting fecal and ingesta contaminants on poultry carcasses," Trans. ASAE 45, 2017-2026 (2002).

W. R. Windham, K. C. Lawrence, B. Park, and R. J. Buhr, "Visible/NIR spectroscopy for characterizing fecal contamination of chicken carcasses," Trans. ASAE 46, 747-751 (2003).

Other

B. W. Calnek, H. John Barnes, C. W. Beard, W. M. Reid, and H. W. Yoder, Diseases of Poultry, 9th ed. (Iowa State U., 1991), Chap. 16, pp. 386-484.

D. Ballard and C. Brown, Computer Vision (Prentice-Hall, 1982), p. 151.

K. Fukunaga, Introduction to Statistical Pattern Recognition, 2nd ed. (Academic, 1992).

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Figures (8)

Fig. 1
Fig. 1

Wavelength band images ( 486.9   nm ) of (a) the first and (b) the second HS cubes with all tumors numbered and marked by rectangles.

Fig. 2
Fig. 2

Enlarged images of tumors 1, 3, 4, and 6, respectively, in Fig. 1(a).

Fig. 3
Fig. 3

Block diagram of the chicken skin tumor detection and fusion system for HS reflectance image data.

Fig. 4
Fig. 4

Detection results (binary lesion images) using the lesion features on the first HS cube with detected tumors marked by rectangles. (a) Before image postprocessing. (b) After image postprocessing.

Fig. 5
Fig. 5

Detection results (binary thickened-skin images) using the thickened-skin features on the first HS cube with detected tumors marked by rectangles. (a) Before image postprocessing. (b) After image postprocessing.

Fig. 6
Fig. 6

Final fused classification image results for the first HS cube with detected tumors marked by rectangles and false alarms marked by circles.

Fig. 7
Fig. 7

Detection result for (a) the lesion features and (b) the thickened-skin features on the second HS cube with detected tumors marked by rectangles.

Fig. 8
Fig. 8

Final fused classification image result on the second HS cube with detected tumors marked by rectangles.

Tables (2)

Tables Icon

Table 1 Best Features Chosen by Two Feature Selection Algorithms for the Lesion and Thickened-Skin Pixel Databases

Tables Icon

Table 2 Pixel Test Data Results for Features Chosen using the FS–MBB Algorithm for the Lesion and Thickened-Skin Pixel Databases

Equations (50)

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21   V
150   W
λ = 447.3
733.5   nm
460 × 600
460 × 400
486.9   nm
65 λ
65 λ
65 λ
65 λ
65 λ
( λ s )
n m
n m
n m
J > B
J < B
( n m ) / 4
J > B
( n m ) / 4
J > B
( n m ) / 2
500 10 , 000
( λ s )
( λ s )
5 × 5
( m = 3 )
( λ s )
P C
P C
K = 3
K = 9
P C
P D
P F A
P C
P C
P C
P C
P D
P C
P C
P C = 90 %
P C
( K = 3 )
< 13
( K = 9 )
P F A
( 486.9   nm )

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