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Computational and Mathematical Methods in Medicine
Volume 2016, Article ID 5689346, 12 pages
http://dx.doi.org/10.1155/2016/5689346
Research Article

A Novel Method for the Separation of Overlapping Pollen Species for Automated Detection and Classification

1Departamento de Posgrado, Instituto Tecnológico Superior de Lerdo, Tecnológico 1555, Placido Domingo, 35150 Lerdo, DG, Mexico
2Departamento de Posgrado, Instituto Tecnológico de la Laguna, Boulevard Revolución, Centro, 27000 Torreón, CO, Mexico

Received 9 December 2015; Accepted 15 February 2016

Academic Editor: Kazuhisa Nishizawa

Copyright © 2016 Santiago Tello-Mijares and Francisco Flores. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Supplementary Material

The dataset and associated ground-truth is composed of 389 images from 12 different pollen species (Table 1). The images are formed using greater magnification and resolution (1388×1040 pixels). The experiments and resulting images are 278×208×3 pixels, as the application is in video format. To obtain the ground-truth, the contours of the pollen grains were manually identified by an expert palynologist. The Supplementary Materials for download contain the entire pollen images database (clases 1–12), the ground-truth (as binary bmp images), results images segmentation (as Matlab figures), Excel descriptors of the features of every pollen, Weka features and associated class for experiment (as ARFF Data File), and segmentation method (as Matlab interface).

  1. Supplementary Material