Leaf disease recognition in vine plants based on local binary patterns and one class support vector machines

IFIP Advances in Information and Communication Technology

Volumn 475, Issue , 2016, Pages 319-327

  Pantazi, Xanthoula Eirini ^a   Moshou, Dimitrios ^a   Tamouridou, Alexandra A ^a   Kasderidis, Stathis ^b  

^a ARISTOTLE UNIVERSITY OF THESSALONIKI   (Greece)

^b i4G Business Incubator   (Greece)

Author keywords

Classifier conflict; Image processing; Novelty detecto; Texture descriptors

Indexed keywords

ARTIFICIAL INTELLIGENCE; FUNGI; IMAGE PROCESSING; SUPPORT VECTOR MACHINES;

DIGITAL PICTURE; LOCAL BINARY PATTERNS; NATURAL COMPLEXES; NOVELTY DETECTO; ONE-CLASS SUPPORT VECTOR MACHINE; POWDERY MILDEW; SMART-PHONE CAMERAS; TEXTURE DESCRIPTORS;

PLANTS (BOTANY);

EID: 84988494051     PISSN: 18684238     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-319-44944-9_27     Document Type: Conference Paper

References (9)

1. Belhumeur, P.N., et al.: Searching the world’s herbaria: a system for visual identification of plant species. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part IV. LNCS, vol. 5305, pp. 116–129. Springer, Heidelberg (2008)
2. Fiel, S., Sablatnig, R.: Automated identication of tree species from images of the bark, leaves and needles. In: Proceedings of 16th Computer Vision Winter Workshop, Mitterberg, Austria, pp. 1–6 (2011)
3. Kumar, N., Belhumeur, P.N., Biswas, A., Jacobs, D.W., Kress, W., Lopez, I.C., Soares, J.V.: Leafsnap: a computer vision system for automatic plant species identification. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012, Part II. LNCS, vol. 7573, pp. 502–516. Springer, Heidelberg (2012)
4. Rother, C., Kolmogorov, V., Blake, A.: GrabCut: interactive foreground extraction using iterated graph cuts. ACM Trans. Graph. 23, 309–314 (2004)
5. Li, J., Wu, W., Wang, T., Zhang, Y.: One step beyond histograms: image representation using Markov stationary features. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–8 (2008)
6. Llado, X., Oliver, A., Freixenet, J., Marti, R., Marti, J.: A textural approach for mass false positive reduction in mammography. Comput. Med. Imaging Graph. 33, 415–422 (2009)
7. Tax, D., Duin, R.: Support vector data description. Mach. Learn. 54(1), 45–66 (2004)
8. Schölkopf, B., Platt, J.C., Shawe-Taylor, J., Smola, A.J., Williamson, R.C.: Estimating the support of a high-dimensional distribution. Neural Comput. 13(7), 1443–1471 (2001)
9. Sachs, A., Thiel, C., Schwenker, F.: One-class support-vector machines for the classification of bioacoustic time series. ICGST Int. J. Artif. Intell. Mach. Learn. (AIML) 6(4), 29–34 (2006)