Identification and determination of the number of immature green citrus fruit in a canopy under different ambient light conditions

Biosystems Engineering

Volumn 117, Issue C, 2014, Pages 51-61

  Sengupta, Subhajit ^a   Lee, Won Suk ^a  

^a University of Florida   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMIC TECHNIQUES; AUTOMATIC DETECTION; CANNY EDGE DETECTION; CONNECTED COMPONENT ALGORITHM; PARTIAL OCCLUSIONS; SCALE INVARIANT FEATURE TRANSFORM ALGORITHMS (SIFT); SHAPE IRREGULARITY; TEXTURE CLASSIFICATION;

ALGORITHMS; COMPOSTING; EDGE DETECTION; FORESTRY; IMAGE RETRIEVAL; MAPPING; SUPPORT VECTOR MACHINES; TEXTURES;

CITRUS FRUITS;

ALGORITHMS; CITRUS FRUITS; COMPOSTING; FORESTRY; IMAGE ANALYSIS; MAPPING; TEXTURE;

EID: 84890841492     PISSN: 15375110     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.biosystemseng.2013.07.007     Document Type: Article

References (35)

1. Aggelopoulou A.D., Bochtis D., Fountas S., Swain K.C., Gemtos T.A., Nanos G.D. Yield prediction in apple orchards based on image processing. Precision Agriculture 2011, 12(3):448-456.
2. Annamalai P., Lee W.S. Identification of green citrus fruits using spectral characteristics 2004, ASAE paper no. FL04-1001, ASAE, St. Joseph, MI, USA.
3. Ballard D.H. Generalizing the Hough transform to detect arbitrary shapes. Pattern Recognition 1981, 13(2):111-122.
4. Bishop C.M. Pattern recognition and machine learning 2006, Springer, New York, NW.
5. Burges C.J. A tutorial on support vector machines for pattern recognition. Data Mining and Knowledge Discovery 1998, 2(2):121-167. Springer.
6. Canny J. A computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 1986, 8(6).
7. Image databases: Search and retrieval of digital imagery 2002, Wiley, New York. V. Castelli, L.D. Bergman (Eds.).
8. Cormen T.H., Leiserson C.E., Rivest R.L., Stein C. Introduction to algorithms 2001, MIT Press.
9. Cortes C., Vapnik V.N. Support-vector networks. Machine Learning 1995, 20.
10. Cubero S., Aleixos N., Moltó E., Gómez-Sanchis J., Blasco J. Advances in machine vision applications forautomatic inspection and quality evaluation of fruitsandvegetables. Food and Bioprocess Technology 2011, 4(4):487-504.
11. Cubero S., Aleixos N., Albert F., Torregrosa A., Ortiz C., García-Navarrete O., et al. Optimised computer vision system for automatic pre-grading of citrus fruit in the field using a mobile platform. Precision Agriculture 2013, 10.1007/s11119-013-9324-7.
12. Duda R., Hart P., Stork D. Pattern classification 2000, Wiley, New York, USA. 2nd ed.
13. Fernandez-Maloigne C., Laugier D., Boscolo C. Detection of apples with texture analyses for an apple pickerrobot. Intelligent vehicles '93 symposium 1993, 323-328.
14. Hopcroft J., Tarjan R. Efficient algorithms for graph manipulation. Communications of the ACM 1973, 16(6):372-378.
15. Jiménez A.R., Ceres R., Pons J.L. A survey of computer vision methods for locating fruit on trees. Transactions of the ASAE 2000, 43(6):1911-1920.
16. Joachims T. Making large-scale SVM learning practical 1998, LS8-report 24, Universität Dortmund, LS VIII-report.
17. Kimme C., Ballard D.H., Sklansky J. Finding circles by an array of accumulators. Communications of the Association for Computing Machinery 1975, 18:120-122.
18. Kurtulmus F., Lee W.S., Vardar A. Green citrus detection using 'eigenfruit', color and circular Gabor texture features under natural outdoor conditions. Computers and Electronics in Agriculture 2011, 78(2):140-149.
19. Lowe D.G. Object recognition from local scale-invariant features. Proceedings of the International Conference on Computer Vision 1999, 2:1150-1157.
20. Lowe D.G. Distinctive image features from scale invariant features. International Journal of Computer Vision 2004, 60(2):91-110.
21. Open Source Computer Vision Library (OpenCV 2.2.0). (2011). Available online and Accessed 10.06.11. http://sourceforge.net/projects/opencvlibrary/files/opencv-win/2.2/.
22. Pla F., Juste F., Ferri F. Feature extraction of spherical objects in image analysis: an application to robotic citrus harvesting. Computers and Electronics in Agriculture 1993, 8:57-72.
23. Rakuna J., Stajnkoa D., Zazulab D. Detecting fruits in natural scenes by using spatial-frequency based texture analysis and multiview geometry. Computers and Electronics in Agriculture 2010, 76(1):80-88.
24. Safren O., Alchanatis V., Ostrovsky V., Levi O. Detection of green apples in hyperspectral images of apple-tree foliage using machine vision. Transactions of the ASABE 2007, 50(6):2303-2313.
25. Schertz C.E., Brown G.K. Basic considerations in mechanizing citrus harvest. Transactions of the ASAE 1968, 11(3):343-346.
26. Schölkopf B., Burges C., Smola A. Advances in kernel methods - Support vector learning 1999, MIT-Press.
27. Sonka M., Hlavac V., Boyle R. Image processing, analysis, and machine vision 1999, 256-260. Brooks/Cole Publishing, CA, USA. 2nd ed.
28. Stajnko D., Lakota M., Hocevar M. Estimation of number and diameter of apple fruits in an orchard during the growing season by thermal imaging. Computers and Electronics in Agriculture 2004, 42:31-42.
29. Tabb A.L., Peterson D.L., Park J. Segmentation of apple fruit from video via background modeling 2006, ASABE paper number 063060, ASABE, St. Joseph, MI, USA.
30. Tamura H., Mori S., Yamawaki T. Texture features corresponding to visual perception. IEEE Transactions on Systems, Man, and Cybernetics, SMC 1978, 8(6):460-473.
31. United States Department of Agriculture-National Agricultural Statistics Service (USDA-NASS) Florida citrus statistics 2009-2010 Available online, Retrieved 10.10.11. http://www.nass.usda.gov/Statistics_by_State/Florida/Publications/Citrus/fcs/2009-10/fcs0910.pdf.
32. Vidal A., Talens P., Prats-Montalbán J.M., Cubero S., Albert F., Blasco J. In-line estimation of the standard colour index of citrus fruits using a computer vision system developed for a mobile platform. Food and Bioprocess Technology 2012, 10.1007/s11947-012-1015-2.
33. Wachs J.P., Stern H.I., Burks T., Alchanatis V. Low and high-level visual feature-based apple detection from multi-modal images. Precision Agriculture 2010, 11(6):717-735.
34. Whittaker A.D., Miles G.E., Mitchell O.R., Gaultney L.D. Fruit location in a partially occluded image. Transactions of the ASAE 1987, 30:591-597.
35. Wikipedia Scale-invariant feature transform Available online, Accessed 10.07.011. http://en.wikipedia.org/wiki/Scale-invariant_feature_transform.