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Classification of honeybee pollen using a multiscale texture filtering scheme

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Abstract.

People are interested in the composition of honeybee pollen due to its nutritional value and therapeutic benefits. Its palynological composition depends on the local flora surrounding the beehive, and its identification is currently done manually using optical microscopy. This procedure is tedious and expensive in systematic application and is unable to automatically separate pollen loads of different species of plants. We present an automatic methodology to discriminate pollen loads based on texture image classification. Texture features are generated using a multiscale filtering scheme. A statistical evaluation of the algorithm is provided and discussed.

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Authors and Affiliations

  1. Departamento de Informática, Universidade de Vigo, Campus Universitario As Lagoas, 32004, Ourense, Spain

    P. Carrión, E. Cernadas, J. F. Gálvez & M. Damián

  2. Departamento de Bioloxía Vexetal e Ciencias do Solo, Universidade de Vigo, Campus Universitario As Lagoas, 32004, Ourense, Spain

    P. de Sá-Otero

Authors
  1. P. Carrión
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  2. E. Cernadas
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  3. J. F. Gálvez
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  4. M. Damián
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  5. P. de Sá-Otero
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Corresponding author

Correspondence to P. Carrión.

Additional information

Received: 26 January 2003, Accepted: 2 March 2004, Published online: 13 July 2004

Correspondence to: P. Carrión

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Carrión, P., Cernadas, E., Gálvez, J.F. et al. Classification of honeybee pollen using a multiscale texture filtering scheme. Machine Vision and Applications 15, 186–193 (2004). https://doi.org/10.1007/s00138-004-0150-9

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  • DOI: https://doi.org/10.1007/s00138-004-0150-9

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