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Classification of Pollen Apertures Using Bag of Words

  • Gildardo Lozano-Vega
  • Yannick Benezeth
  • Franck Marzani
  • Frank Boochs
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8156)

Abstract

The taxonomical recognition of microscopic biological particles such as pollen and spores is relevant for medical and aerobiological applications. Focusing on an accurate and automatic vision-based pollen recognition system, we propose a method for classification of pollen apertures based on bag-of-words strategy, with the ability of learning new types from different taxa without the need of new algorithms. Results demonstrate suitable performance and ability to add new taxa.

Keywords

pattern recognition classification local jets bag of words apertures palynology 

References

  1. 1.
    Erdtman, G.: An Introduction To Pollen Analysis. Chronica Botanica Company, USA (1943)Google Scholar
  2. 2.
    Hesse, M., Halbritter, H., Weber, M., Buchner, R., Frosch- Radivo, A., Ulrich, S.: Pollen Terminology. In: An Illustrated Handbook, Springer, Austria (2009)Google Scholar
  3. 3.
    Boucher, A., Hidalgo, P.J., Thonnat, M., Belmonte, J., Galan, C., Bonton, P., Tomczak, R.: Development of a semi-automatic system for pollen recognition. Aerobiologia 18(3), 195–201 (2002)CrossRefGoogle Scholar
  4. 4.
    Chen, C., Hendriks, E.A., Duin, R.P., Reiber, J., Hiemstra, P., De Weger, L., Stoel, B.: Feasibility study on automated recognition of allergenic pollen: grass, birch and mugwort. Aerobiologia 22, 275–284 (2006)CrossRefGoogle Scholar
  5. 5.
    Csurka, G., Dance, C., Bray, C., Fan, L., Willamowski, J.: Visual categorization with bags of keypoints. In: Pattern Recognition and Machine Learning in Computer Vision Workshop, ECCV Grenoble, France, pp. 1–22 (2004)Google Scholar
  6. 6.
    Wu, J., Tan, W.-C., Rehg, J.M.: Efficient and Effective Visual Codebook Generation Using Additive Kernels. Journal of Machine Learning Research 12, 3097–3118 (2011), Georgia Institute of TechnologyGoogle Scholar
  7. 7.
    López-Sastre, R.J., Tuytelaars, T., Acevedo-Rodríguez, F.J., Maldonado-Bascón, S.: Towards a more discriminative and semantic visual vocabulary. Computer Vision and Image Understanding 115, 415–425 (2011)CrossRefGoogle Scholar
  8. 8.
    Mikolajczyk, K., Schmid, C.: A performance evaluation of local descriptors. IEEE Transactions on Pattern Analysis and Machine Intelligence 27, 1615–1630 (2005)CrossRefGoogle Scholar
  9. 9.
    Schmid, C., Mohr, R.: Local grayvalue invariants for image retrieval. IEEE Transactions on Pattern Analysis and Machine Intelligence 19(5), 530–535 (1997)CrossRefGoogle Scholar
  10. 10.
    Koenderink, J.J., Doorn, A.J.: Representation of local geometry in the visual system. Biological Cybernetics 5(6), 367–375 (1987)CrossRefGoogle Scholar
  11. 11.
    Grauman, K., Darrell, T.: Pyramid matching kernel: Discriminative classification with sets of image features. In: Tenth IEEE International Conference on Computer Vision, ICCV 2005, vol. 2, pp. 1458–1465 (2005)Google Scholar
  12. 12.
    Lazebnik, S., Schmid, C., Ponce, J.: Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006, vol. 2, pp. 2169–2178 (2006)Google Scholar
  13. 13.
    Byun, H.-R., Lee, S.-W.: Applications of support vector machines for pattern recognition: A survey. In: Lee, S.-W., Verri, A. (eds.) SVM 2002. LNCS, vol. 2388, pp. 213–236. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  14. 14.
    Teague, M.R.: Image analysis via the general theory of moments. Optical Society of America 70(8), 920–930 (1979)MathSciNetCrossRefGoogle Scholar
  15. 15.
    Vorobyov, M.: Shape Classification Using Zernike Moments. Technical Report. iCamp-University of California Irvine (2011)Google Scholar
  16. 16.
    Lowe, D.: Distinctive image features from scale-invariant keypoints. In: IJCV (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Gildardo Lozano-Vega
    • 1
    • 2
  • Yannick Benezeth
    • 2
  • Franck Marzani
    • 2
  • Frank Boochs
    • 1
  1. 1.i3mainz, Fachhochschule MainzMainzGermany
  2. 2.Le2i, Université de BourgogneDijon CedexFrance

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