Detecting citrus canker by hyperspectral reflectance imaging and spectral information divergence

American Society of Agricultural and Biological Engineers Annual International Meeting 2008, ASABE 2008

Volumn 6, Issue , 2008, Pages 3247-3261

  Qin, Jianwei ^a   Burks, Thomas F ^a   Ritenour, Mark A ^b   Bonn, Gordon W ^c  

^a University of Florida   (United States)

^b UNIVERSITY OF FLORIDA   (United States)

^c FLORIDA DEPARTMENT OF AGRICULTURE AND CONSUMER SERVICES   (United States)

Author keywords

Citrus canker; Disease detection; Food safety; Hyperspectral imaging; Spectral similarity

Indexed keywords

CORUNDUM; FRUITS; IMAGE ANALYSIS; IMAGING TECHNIQUES; OPTOELECTRONIC DEVICES; REFLECTION;

CITRUS CANKER; DISEASE DETECTION; FOOD SAFETY; HYPERSPECTRAL IMAGING; SPECTRAL SIMILARITY;

IMAGE CLASSIFICATION;

EID: 63049136363     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (20)

1. Aleixos, N., J. Blasco, F. Navarron, and E. Molto. 2002. Multispectral inspection of citrus in realtime using machine vision and digital signal processors. Comput. Electron. Agri. 33(2): 121-137.
2. Ariana, D. P., R. Lu, and D. E. Guyer. 2006. Near-infrared hyperspectral reflectance imaging for detection of bruises on pickling cucumbers. Comput. Electron. Agri. 53(1): 60-70.
3. Blasco, J., N. Aleixos, J. Gomez, and E. Molto. 2007. Citrus sorting by identification of the most common defects using multispectral computer vision. J. Food Eng. 83(3): 384-393.
4. Chao, K., C. C. Yang, Y. R. Chen, M. S. Kim, and D. E. Chan. 2007. Fast line-scan imaging system for broiler carcass inspection. Sens. Instrum. Food Qual. Saf. 1(2): 62-71.
5. Chang, C.-l. 2000. An information theoretic-based approach to spectral variability, similarity and discriminability for hyperspectral image analysis. IEEE Trans. Inf. Theory 46(5): 1927- 1932.
6. Edwards, J. G., and C. H. Sweet. 1986. Citrus blight assessment using a microcomputer: quantifying damage using an apple computer to solve reflectance spectra of entire trees. Florida Scientist 49 (1): 48-53.
7. Gaffney, J. J. 1973. Reflectance properties of citrus fruits. Trans. ASAE 16(2): 310-314.
8. Gomez, J., J. Blasco, E. Molto, and G. Camps-Vails. 2007. Hyperspectral detection of citrus damage with Mahalanobis kernel classifier. Electron. Lett. 43(20): 1082-1084.
9. Kim, M. S., Y. R. Chen, and P. M. Mehl. 2001. Hyperspectral reflectance and fluorescence imaging system for food quality and safety. Trans. ASAE 44(3): 721-729.
10. Kim, M. S., A. M. Lefcourt, K. Chao, Y. R. Chen, I. Kim, and D. E. Chan. 2002. Multispectral detection of fecal contamination on apples based on hyperspectral imagery. Part I. Application of visible and near-infrared reflectance imaging. Trans. ASAE 45(6): 2027- 2037.
11. Lawrence, K. C, S. C. Yoon, G. W. Heitschmidt, D. R. Jones, and B. Park. 2008. Imaging system with modified-pressure chamber for crack detection in shell eggs. Sens. Instrum. Food Qual. Saf., doi: 10.1007/s11694-008-9039-z.
12. Lu, R. 2003. Detection of bruises on apples using near-infrared hyperspectral imaging. Trans. ASAE 46(2): 523-530.
13. Lu, R. and Y. R. Chen. 1998. Hyperspectral imaging for safety inspection of food and agricultural products. SPIE: 3544: 121-133.
14. Miller, W. M. and G. P. Drouillard. 2001. Multiple feature analysis for machine vision grading of Florida citrus. Applied Eng. Agri. 17(5): 627-633.
15. Park, B., W. R. Windham, K. C. Lawrence, and D. P. Smith. 2007. Contaminant classification of poultry hyperspectral imagery using a spectral angle mapper algorithm. Biosyst. Eng. 96(3): 323-333.
16. Pydipati, R., T. F. Burks, and W. S. Lee. 2006. Identification of citrus disease using color texture features and discriminant analysis. Comput. Electron. Agri. 52(1-2): 49-59.
17. Qin, J. and R. Lu. 2005. Detection of pits in tart cherries by hyperspectral transmission imaging. Trans. ASAE 48(5): 1963-1970.
18. Schubert, T. S., S. A. Rizvi, X. A. Sun, T. R. Gottwald, J. H. Graham, and W. N. Dixon. 2001. Meeting the challenge of eradicating citrus canker in Florida - Again. Plant Dis. 85(4): 340-356.
19. van der Meer, F. 2006. The effectiveness of spectral similarity measures for the analysis of hyperspectral imagery. Int. J. Appl. Earth Obs. Geoinfo. 8(1): 3-17.
20. Yang, C., J. H. Everitt, and J. M. Bradford. 2008. Yield estimation from hyperspectral imagery using spectral angle mapper (SAM). Trans. ASABE 51(2): 729-737.