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Classification of coral reef images from underwater video using neural networks

Ma. Shiela Angeli C. Marcos, Maricor N. Soriano, and Caesar A. Saloma

Open Access Open Access

Abstract

We use a feedforward backpropagation neural network to classify close-up images of coral reef components into three benthic categories: living coral, dead coral and sand. We have achieved a success rate of 86.5% (false positive = 6.7%) for test images that were not in the training set which is high considering that corals occur in an immense variety of appearance. Color and texture features derived from video stills of coral reef transects from the Great Barrier Reef were used as inputs to the network. We also developed a rule-based decision tree classifier according to how marine scientists classify corals from texture and color, and obtained a lower recognition rate of 79.7% for the same set of images.

©2005 Optical Society of America

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References

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  • Year
  • Author
  • Publication
  1. R. Kenchington and B. Hudson , Coral Reef Management Handbook ( UNESCO 1984 ).
  2. S. J. Purkis , “ A ‘reef-up’ approach to classifying coral habitats from IKONOS imagery ,” IEEE Trans. Geosci. Remote Sens.   43 , 1375 – 1390 ( 2005 ).
    [Crossref]
  3. E. J. Hochberg and M. J. Atkinson , “ Spectral discrimination of coral reef benthic communities ,” Coral Reefs   19 , 164 – 171 ( 2000 ).
    [Crossref]
  4. E. P. Green , P. J. Mumby , A. J. Edwards , and C. D. Clark , “ A review of remote sensing for the assessment and management of tropical coastal resources ,” Coastal Management   24 , 1 – 40 ( 1996 ).
    [Crossref]
  5. A. Uychiaco , P. Alino , and M. Atrigenio , “ Video and Other Monitoring Techniques for Coral Reef Communities ,” in the Proceedings of the 3rd ASEAN Science and Technology Week Conference, Marine Science: Living Coastal Resources , L. M. Chou and C. R. Wilkinson , ed. ( National University of Singapore and National Science and Technology Board, Singapore , 1992 ) pp. 35 – 40 .
  6. T. Carleton and J Done , “ Qualitative video sampling of coral reef benthos: large-scale application ,” Coral Reefs   14 , 35 – 46 ( 1995 ).
    [Crossref]
  7. A. Olmos and E. Trucco , “ Detecting man-made objects in unconstrained subsea videos ,” in the Proceedings of the British Machine Video Conference 2002 , P. L. Rosin and A. D. Marshall , ed. ( Cardiff, U. K. , 2002 ) pp. 517 – 526 .
  8. M. J. Rendas , M. Thomson , and S. Rolfes , “ Maerl mapping with an underwater vehicle using vision ,” presented in the International Symposium on Environmental Software Systems, Semmering, Austria, 27-30 May 2003.
  9. V. Di Gesu , F. Isgro , D. Tegolo , and E. Trucco , “ Finding essential features for tracking starfish in video sequence ,” in the Proceedings of the 12 th IEEE International Conference on Image Analysis and Processing 0 , M. Ferretti and M. Grazia Albanesi , ed. ( Mantova, Italy , 2003 ) pp. 504 – 509 .
  10. M. Soriano , S. Marcos , C. Saloma , M. Quibilan , and P. Aliño , “ Image classification of coral reef components from underwater color video ,” in the Proceedings of the MTS/IEEE OCEANS Conference ( Honolulu, Hawaii , 2001 ) pp. 1008 – 1013 .
  11. R. Duda , P. Hart , and D. Stork , Pattern Classification 2 nd Edition ( John Wiley and Sons Inc., Canada , 2001 ).
  12. A. M. Darwish and A. Jain , “ A Rule Based Approach for Visual Pattern Inspection ,” IEEE Trans. Pattern. Anal. Mach. Intell.   10 (1), 56 – 68 ( 1988 ).
    [Crossref]
  13. S. Katsuragawa , K. Doi , H. MacMahon , L. Monnier-Cholley , T. Ishida , and T. Kobayashi , “ Classification of normal and abnormal lungs with interstitial diseases by rule-based method and artificial neural networks ,” Journal of Digital Imaging   10 (3), 108 – 14 ( 1997 ).
    [Crossref] [PubMed]
  14. M. Swain and D. Ballard , “ Color indexing ,” International J. Computer Vision   7 , 11 – 32 ( 1991 ).
    [Crossref]
  15. M. Soriano , L. Garcia , and C. A. Saloma , “ Fluorescent image classification by major color histograms and a neural network ,” Opt. Express   8 , 271 – 277 ( 2001 ), http://www.opticsexpress.org/abstract.cfm?URI=OPEX-8-5-271 .
    [Crossref] [PubMed]
  16. I. Pitas , Digital Image Processing Algorithms ( Prentice Hall, London 1993 ).
  17. T. Ojala , M. Pietikainen , and T. Maenpaa , “ Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns ,” IEEE Trans Pattern Analysis and Machine Intelligence   24 (7), 971 – 987 ( 2002 ).
    [Crossref]
  18. S. Haykin , Neural Networks: A Comprehensive Foundation 1 st Edition ( Prentice Hall, New Jersey, USA , 1994 ).

2005 (1)

S. J. Purkis , “ A ‘reef-up’ approach to classifying coral habitats from IKONOS imagery ,” IEEE Trans. Geosci. Remote Sens.   43 , 1375 – 1390 ( 2005 ).
[Crossref]

2002 (1)

T. Ojala , M. Pietikainen , and T. Maenpaa , “ Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns ,” IEEE Trans Pattern Analysis and Machine Intelligence   24 (7), 971 – 987 ( 2002 ).
[Crossref]

2001 (2)

M. Soriano , L. Garcia , and C. A. Saloma , “ Fluorescent image classification by major color histograms and a neural network ,” Opt. Express   8 , 271 – 277 ( 2001 ), http://www.opticsexpress.org/abstract.cfm?URI=OPEX-8-5-271 .
[Crossref] [PubMed]

M. Soriano , S. Marcos , C. Saloma , M. Quibilan , and P. Aliño , “ Image classification of coral reef components from underwater color video ,” in the Proceedings of the MTS/IEEE OCEANS Conference ( Honolulu, Hawaii , 2001 ) pp. 1008 – 1013 .

2000 (1)

E. J. Hochberg and M. J. Atkinson , “ Spectral discrimination of coral reef benthic communities ,” Coral Reefs   19 , 164 – 171 ( 2000 ).
[Crossref]

1997 (1)

S. Katsuragawa , K. Doi , H. MacMahon , L. Monnier-Cholley , T. Ishida , and T. Kobayashi , “ Classification of normal and abnormal lungs with interstitial diseases by rule-based method and artificial neural networks ,” Journal of Digital Imaging   10 (3), 108 – 14 ( 1997 ).
[Crossref] [PubMed]

1996 (1)

E. P. Green , P. J. Mumby , A. J. Edwards , and C. D. Clark , “ A review of remote sensing for the assessment and management of tropical coastal resources ,” Coastal Management   24 , 1 – 40 ( 1996 ).
[Crossref]

1995 (1)

T. Carleton and J Done , “ Qualitative video sampling of coral reef benthos: large-scale application ,” Coral Reefs   14 , 35 – 46 ( 1995 ).
[Crossref]

1991 (1)

M. Swain and D. Ballard , “ Color indexing ,” International J. Computer Vision   7 , 11 – 32 ( 1991 ).
[Crossref]

1988 (1)

A. M. Darwish and A. Jain , “ A Rule Based Approach for Visual Pattern Inspection ,” IEEE Trans. Pattern. Anal. Mach. Intell.   10 (1), 56 – 68 ( 1988 ).
[Crossref]

Alino, P.

A. Uychiaco , P. Alino , and M. Atrigenio , “ Video and Other Monitoring Techniques for Coral Reef Communities ,” in the Proceedings of the 3rd ASEAN Science and Technology Week Conference, Marine Science: Living Coastal Resources , L. M. Chou and C. R. Wilkinson , ed. ( National University of Singapore and National Science and Technology Board, Singapore , 1992 ) pp. 35 – 40 .

Aliño, P.

M. Soriano , S. Marcos , C. Saloma , M. Quibilan , and P. Aliño , “ Image classification of coral reef components from underwater color video ,” in the Proceedings of the MTS/IEEE OCEANS Conference ( Honolulu, Hawaii , 2001 ) pp. 1008 – 1013 .

Atkinson, M. J.

E. J. Hochberg and M. J. Atkinson , “ Spectral discrimination of coral reef benthic communities ,” Coral Reefs   19 , 164 – 171 ( 2000 ).
[Crossref]

Atrigenio, M.

A. Uychiaco , P. Alino , and M. Atrigenio , “ Video and Other Monitoring Techniques for Coral Reef Communities ,” in the Proceedings of the 3rd ASEAN Science and Technology Week Conference, Marine Science: Living Coastal Resources , L. M. Chou and C. R. Wilkinson , ed. ( National University of Singapore and National Science and Technology Board, Singapore , 1992 ) pp. 35 – 40 .

Ballard, D.

M. Swain and D. Ballard , “ Color indexing ,” International J. Computer Vision   7 , 11 – 32 ( 1991 ).
[Crossref]

Carleton, T.

T. Carleton and J Done , “ Qualitative video sampling of coral reef benthos: large-scale application ,” Coral Reefs   14 , 35 – 46 ( 1995 ).
[Crossref]

Clark, C. D.

E. P. Green , P. J. Mumby , A. J. Edwards , and C. D. Clark , “ A review of remote sensing for the assessment and management of tropical coastal resources ,” Coastal Management   24 , 1 – 40 ( 1996 ).
[Crossref]

Darwish, A. M.

A. M. Darwish and A. Jain , “ A Rule Based Approach for Visual Pattern Inspection ,” IEEE Trans. Pattern. Anal. Mach. Intell.   10 (1), 56 – 68 ( 1988 ).
[Crossref]

Di Gesu, V.

V. Di Gesu , F. Isgro , D. Tegolo , and E. Trucco , “ Finding essential features for tracking starfish in video sequence ,” in the Proceedings of the 12 th IEEE International Conference on Image Analysis and Processing 0 , M. Ferretti and M. Grazia Albanesi , ed. ( Mantova, Italy , 2003 ) pp. 504 – 509 .

Doi, K.

S. Katsuragawa , K. Doi , H. MacMahon , L. Monnier-Cholley , T. Ishida , and T. Kobayashi , “ Classification of normal and abnormal lungs with interstitial diseases by rule-based method and artificial neural networks ,” Journal of Digital Imaging   10 (3), 108 – 14 ( 1997 ).
[Crossref] [PubMed]

Done, J

T. Carleton and J Done , “ Qualitative video sampling of coral reef benthos: large-scale application ,” Coral Reefs   14 , 35 – 46 ( 1995 ).
[Crossref]

Duda, R.

R. Duda , P. Hart , and D. Stork , Pattern Classification 2 nd Edition ( John Wiley and Sons Inc., Canada , 2001 ).

Edwards, A. J.

E. P. Green , P. J. Mumby , A. J. Edwards , and C. D. Clark , “ A review of remote sensing for the assessment and management of tropical coastal resources ,” Coastal Management   24 , 1 – 40 ( 1996 ).
[Crossref]

Garcia, L.

Green, E. P.

E. P. Green , P. J. Mumby , A. J. Edwards , and C. D. Clark , “ A review of remote sensing for the assessment and management of tropical coastal resources ,” Coastal Management   24 , 1 – 40 ( 1996 ).
[Crossref]

Hart, P.

R. Duda , P. Hart , and D. Stork , Pattern Classification 2 nd Edition ( John Wiley and Sons Inc., Canada , 2001 ).

Haykin, S.

S. Haykin , Neural Networks: A Comprehensive Foundation 1 st Edition ( Prentice Hall, New Jersey, USA , 1994 ).

Hochberg, E. J.

E. J. Hochberg and M. J. Atkinson , “ Spectral discrimination of coral reef benthic communities ,” Coral Reefs   19 , 164 – 171 ( 2000 ).
[Crossref]

Hudson, B.

R. Kenchington and B. Hudson , Coral Reef Management Handbook ( UNESCO 1984 ).

Isgro, F.

V. Di Gesu , F. Isgro , D. Tegolo , and E. Trucco , “ Finding essential features for tracking starfish in video sequence ,” in the Proceedings of the 12 th IEEE International Conference on Image Analysis and Processing 0 , M. Ferretti and M. Grazia Albanesi , ed. ( Mantova, Italy , 2003 ) pp. 504 – 509 .

Ishida, T.

S. Katsuragawa , K. Doi , H. MacMahon , L. Monnier-Cholley , T. Ishida , and T. Kobayashi , “ Classification of normal and abnormal lungs with interstitial diseases by rule-based method and artificial neural networks ,” Journal of Digital Imaging   10 (3), 108 – 14 ( 1997 ).
[Crossref] [PubMed]

Jain, A.

A. M. Darwish and A. Jain , “ A Rule Based Approach for Visual Pattern Inspection ,” IEEE Trans. Pattern. Anal. Mach. Intell.   10 (1), 56 – 68 ( 1988 ).
[Crossref]

Katsuragawa, S.

S. Katsuragawa , K. Doi , H. MacMahon , L. Monnier-Cholley , T. Ishida , and T. Kobayashi , “ Classification of normal and abnormal lungs with interstitial diseases by rule-based method and artificial neural networks ,” Journal of Digital Imaging   10 (3), 108 – 14 ( 1997 ).
[Crossref] [PubMed]

Kenchington, R.

R. Kenchington and B. Hudson , Coral Reef Management Handbook ( UNESCO 1984 ).

Kobayashi, T.

S. Katsuragawa , K. Doi , H. MacMahon , L. Monnier-Cholley , T. Ishida , and T. Kobayashi , “ Classification of normal and abnormal lungs with interstitial diseases by rule-based method and artificial neural networks ,” Journal of Digital Imaging   10 (3), 108 – 14 ( 1997 ).
[Crossref] [PubMed]

MacMahon, H.

S. Katsuragawa , K. Doi , H. MacMahon , L. Monnier-Cholley , T. Ishida , and T. Kobayashi , “ Classification of normal and abnormal lungs with interstitial diseases by rule-based method and artificial neural networks ,” Journal of Digital Imaging   10 (3), 108 – 14 ( 1997 ).
[Crossref] [PubMed]

Maenpaa, T.

T. Ojala , M. Pietikainen , and T. Maenpaa , “ Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns ,” IEEE Trans Pattern Analysis and Machine Intelligence   24 (7), 971 – 987 ( 2002 ).
[Crossref]

Marcos, S.

M. Soriano , S. Marcos , C. Saloma , M. Quibilan , and P. Aliño , “ Image classification of coral reef components from underwater color video ,” in the Proceedings of the MTS/IEEE OCEANS Conference ( Honolulu, Hawaii , 2001 ) pp. 1008 – 1013 .

Monnier-Cholley, L.

S. Katsuragawa , K. Doi , H. MacMahon , L. Monnier-Cholley , T. Ishida , and T. Kobayashi , “ Classification of normal and abnormal lungs with interstitial diseases by rule-based method and artificial neural networks ,” Journal of Digital Imaging   10 (3), 108 – 14 ( 1997 ).
[Crossref] [PubMed]

Mumby, P. J.

E. P. Green , P. J. Mumby , A. J. Edwards , and C. D. Clark , “ A review of remote sensing for the assessment and management of tropical coastal resources ,” Coastal Management   24 , 1 – 40 ( 1996 ).
[Crossref]

Ojala, T.

T. Ojala , M. Pietikainen , and T. Maenpaa , “ Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns ,” IEEE Trans Pattern Analysis and Machine Intelligence   24 (7), 971 – 987 ( 2002 ).
[Crossref]

Olmos, A.

A. Olmos and E. Trucco , “ Detecting man-made objects in unconstrained subsea videos ,” in the Proceedings of the British Machine Video Conference 2002 , P. L. Rosin and A. D. Marshall , ed. ( Cardiff, U. K. , 2002 ) pp. 517 – 526 .

Pietikainen, M.

T. Ojala , M. Pietikainen , and T. Maenpaa , “ Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns ,” IEEE Trans Pattern Analysis and Machine Intelligence   24 (7), 971 – 987 ( 2002 ).
[Crossref]

Pitas, I.

I. Pitas , Digital Image Processing Algorithms ( Prentice Hall, London 1993 ).

Purkis, S. J.

S. J. Purkis , “ A ‘reef-up’ approach to classifying coral habitats from IKONOS imagery ,” IEEE Trans. Geosci. Remote Sens.   43 , 1375 – 1390 ( 2005 ).
[Crossref]

Quibilan, M.

M. Soriano , S. Marcos , C. Saloma , M. Quibilan , and P. Aliño , “ Image classification of coral reef components from underwater color video ,” in the Proceedings of the MTS/IEEE OCEANS Conference ( Honolulu, Hawaii , 2001 ) pp. 1008 – 1013 .

Rendas, M. J.

M. J. Rendas , M. Thomson , and S. Rolfes , “ Maerl mapping with an underwater vehicle using vision ,” presented in the International Symposium on Environmental Software Systems, Semmering, Austria, 27-30 May 2003.

Rolfes, S.

M. J. Rendas , M. Thomson , and S. Rolfes , “ Maerl mapping with an underwater vehicle using vision ,” presented in the International Symposium on Environmental Software Systems, Semmering, Austria, 27-30 May 2003.

Saloma, C.

M. Soriano , S. Marcos , C. Saloma , M. Quibilan , and P. Aliño , “ Image classification of coral reef components from underwater color video ,” in the Proceedings of the MTS/IEEE OCEANS Conference ( Honolulu, Hawaii , 2001 ) pp. 1008 – 1013 .

Saloma, C. A.

Soriano, M.

M. Soriano , L. Garcia , and C. A. Saloma , “ Fluorescent image classification by major color histograms and a neural network ,” Opt. Express   8 , 271 – 277 ( 2001 ), http://www.opticsexpress.org/abstract.cfm?URI=OPEX-8-5-271 .
[Crossref] [PubMed]

M. Soriano , S. Marcos , C. Saloma , M. Quibilan , and P. Aliño , “ Image classification of coral reef components from underwater color video ,” in the Proceedings of the MTS/IEEE OCEANS Conference ( Honolulu, Hawaii , 2001 ) pp. 1008 – 1013 .

Stork, D.

R. Duda , P. Hart , and D. Stork , Pattern Classification 2 nd Edition ( John Wiley and Sons Inc., Canada , 2001 ).

Swain, M.

M. Swain and D. Ballard , “ Color indexing ,” International J. Computer Vision   7 , 11 – 32 ( 1991 ).
[Crossref]

Tegolo, D.

V. Di Gesu , F. Isgro , D. Tegolo , and E. Trucco , “ Finding essential features for tracking starfish in video sequence ,” in the Proceedings of the 12 th IEEE International Conference on Image Analysis and Processing 0 , M. Ferretti and M. Grazia Albanesi , ed. ( Mantova, Italy , 2003 ) pp. 504 – 509 .

Thomson, M.

M. J. Rendas , M. Thomson , and S. Rolfes , “ Maerl mapping with an underwater vehicle using vision ,” presented in the International Symposium on Environmental Software Systems, Semmering, Austria, 27-30 May 2003.

Trucco, E.

A. Olmos and E. Trucco , “ Detecting man-made objects in unconstrained subsea videos ,” in the Proceedings of the British Machine Video Conference 2002 , P. L. Rosin and A. D. Marshall , ed. ( Cardiff, U. K. , 2002 ) pp. 517 – 526 .

V. Di Gesu , F. Isgro , D. Tegolo , and E. Trucco , “ Finding essential features for tracking starfish in video sequence ,” in the Proceedings of the 12 th IEEE International Conference on Image Analysis and Processing 0 , M. Ferretti and M. Grazia Albanesi , ed. ( Mantova, Italy , 2003 ) pp. 504 – 509 .

Uychiaco, A.

A. Uychiaco , P. Alino , and M. Atrigenio , “ Video and Other Monitoring Techniques for Coral Reef Communities ,” in the Proceedings of the 3rd ASEAN Science and Technology Week Conference, Marine Science: Living Coastal Resources , L. M. Chou and C. R. Wilkinson , ed. ( National University of Singapore and National Science and Technology Board, Singapore , 1992 ) pp. 35 – 40 .

Coastal Management (1)

E. P. Green , P. J. Mumby , A. J. Edwards , and C. D. Clark , “ A review of remote sensing for the assessment and management of tropical coastal resources ,” Coastal Management   24 , 1 – 40 ( 1996 ).
[Crossref]

Coral Reefs (2)

T. Carleton and J Done , “ Qualitative video sampling of coral reef benthos: large-scale application ,” Coral Reefs   14 , 35 – 46 ( 1995 ).
[Crossref]

E. J. Hochberg and M. J. Atkinson , “ Spectral discrimination of coral reef benthic communities ,” Coral Reefs   19 , 164 – 171 ( 2000 ).
[Crossref]

IEEE Trans Pattern Analysis and Machine Intelligence (1)

T. Ojala , M. Pietikainen , and T. Maenpaa , “ Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns ,” IEEE Trans Pattern Analysis and Machine Intelligence   24 (7), 971 – 987 ( 2002 ).
[Crossref]

IEEE Trans. Geosci. Remote Sens. (1)

S. J. Purkis , “ A ‘reef-up’ approach to classifying coral habitats from IKONOS imagery ,” IEEE Trans. Geosci. Remote Sens.   43 , 1375 – 1390 ( 2005 ).
[Crossref]

IEEE Trans. Pattern. Anal. Mach. Intell. (1)

A. M. Darwish and A. Jain , “ A Rule Based Approach for Visual Pattern Inspection ,” IEEE Trans. Pattern. Anal. Mach. Intell.   10 (1), 56 – 68 ( 1988 ).
[Crossref]

International J. Computer Vision (1)

M. Swain and D. Ballard , “ Color indexing ,” International J. Computer Vision   7 , 11 – 32 ( 1991 ).
[Crossref]

Journal of Digital Imaging (1)

S. Katsuragawa , K. Doi , H. MacMahon , L. Monnier-Cholley , T. Ishida , and T. Kobayashi , “ Classification of normal and abnormal lungs with interstitial diseases by rule-based method and artificial neural networks ,” Journal of Digital Imaging   10 (3), 108 – 14 ( 1997 ).
[Crossref] [PubMed]

Opt. Express (1)

Other (9)

I. Pitas , Digital Image Processing Algorithms ( Prentice Hall, London 1993 ).

S. Haykin , Neural Networks: A Comprehensive Foundation 1 st Edition ( Prentice Hall, New Jersey, USA , 1994 ).

R. Kenchington and B. Hudson , Coral Reef Management Handbook ( UNESCO 1984 ).

A. Uychiaco , P. Alino , and M. Atrigenio , “ Video and Other Monitoring Techniques for Coral Reef Communities ,” in the Proceedings of the 3rd ASEAN Science and Technology Week Conference, Marine Science: Living Coastal Resources , L. M. Chou and C. R. Wilkinson , ed. ( National University of Singapore and National Science and Technology Board, Singapore , 1992 ) pp. 35 – 40 .

A. Olmos and E. Trucco , “ Detecting man-made objects in unconstrained subsea videos ,” in the Proceedings of the British Machine Video Conference 2002 , P. L. Rosin and A. D. Marshall , ed. ( Cardiff, U. K. , 2002 ) pp. 517 – 526 .

M. J. Rendas , M. Thomson , and S. Rolfes , “ Maerl mapping with an underwater vehicle using vision ,” presented in the International Symposium on Environmental Software Systems, Semmering, Austria, 27-30 May 2003.

V. Di Gesu , F. Isgro , D. Tegolo , and E. Trucco , “ Finding essential features for tracking starfish in video sequence ,” in the Proceedings of the 12 th IEEE International Conference on Image Analysis and Processing 0 , M. Ferretti and M. Grazia Albanesi , ed. ( Mantova, Italy , 2003 ) pp. 504 – 509 .

M. Soriano , S. Marcos , C. Saloma , M. Quibilan , and P. Aliño , “ Image classification of coral reef components from underwater color video ,” in the Proceedings of the MTS/IEEE OCEANS Conference ( Honolulu, Hawaii , 2001 ) pp. 1008 – 1013 .

R. Duda , P. Hart , and D. Stork , Pattern Classification 2 nd Edition ( John Wiley and Sons Inc., Canada , 2001 ).

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Figures (5)
Fig. 1.
Fig. 1. The LBP operator. A 3×3 pixel neighborhood (a) is binarized into (b) by thresholding neighboring pixels with the center pixel. Weights in powers of two as in (c) is multiplied to (b) to obtain (d). The LBP value is computed as the sum of neighboring pixel values in (d), e.g. 1+8+32+128 = 169. This value is assigned to the center pixel.

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Fig. 2.
Fig. 2. Rotation invariant pixel neighborhood for LBP8riu2 in (a). Points g6, g4, g8 and g2 are obtained by bilinear interpolation. Binning is achieved through nine uniform patterns in (b) considered for the LBP8riu2 operator (black = 0, white = 1).

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Fig. 3.
Fig. 3. Flowchart of two-step classification scheme for the coral reef images.

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Fig. 4.
Fig. 4. (a) Image of a reef area from video. Shown are: L live coral, D dead coral and S sand/rock. (b) Examples of reef images with different textures. First row, images of regular texture; second row of irregular texture and third row of smooth texture. Images are of different sizes and cropped from image frames of a reef video.

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Fig. 5.
Fig. 5. Confusion matrices of classification performance for the NN and two-step classifier. Each block contains the number of samples classified and beside it is its percentage over the total number of samples in the actual class. The diagonals shown as shaded blocks, indicates successful per class recognition rates. A perfect classifier is perceived as having 100% recognition rate in the diagonal elements. Columns in off-diagonal elements indicate misclassification (false-positive) rates. (a) and (b) reveal results for the NN classifier while (c) presents results for the two-step classifier.

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