@InProceedings{MedeirosNetoBragHarbJúni:2017:DrMeGe,
author = "Medeiros Neto, Francisco Gerardo and Braga, {\'{\I}}talo
Rodrigues and Harber, Matthew Henry and J{\'u}nior, I{\'a}lis
Cavalcante de Paula",
affiliation = "{Federal University of Cear{\'a}} and {Federal University of
Cear{\'a}} and GeoPoll and {Federal University of Cear{\'a}}",
title = "Drosophila melanogaster Gender Classification Based on Fractal
Dimension",
booktitle = "Proceedings...",
year = "2017",
editor = "Torchelsen, Rafael Piccin and Nascimento, Erickson Rangel do and
Panozzo, Daniele and Liu, Zicheng and Farias, Myl{\`e}ne and
Viera, Thales and Sacht, Leonardo and Ferreira, Nivan and Comba,
Jo{\~a}o Luiz Dihl and Hirata, Nina and Schiavon Porto, Marcelo
and Vital, Creto and Pagot, Christian Azambuja and Petronetto,
Fabiano and Clua, Esteban and Cardeal, Fl{\'a}vio",
organization = "Conference on Graphics, Patterns and Images, 30. (SIBGRAPI)",
publisher = "IEEE Computer Society",
address = "Los Alamitos",
keywords = "stationary wavelet transform, Canny filter, fractal dimension,
classification.",
abstract = "Biometrics, previously used only in human identification, can help
experts in the analysis of biological images. Flies of the genus
Drosophila have become model organisms by almost global presence
and short life cycle. Facial recognition techniques and geometric
morphometry can be used in image processing for classification.
The latter requires human interaction. This work details a
methodology based on stationary wavelet transform, Canny filter
and fractal dimension aimed to infer the gender of Drosophila
melanogaster based on images of their wings. The combination of
variation in the training and test samples and classification
methods showed the proposed algorithms accuracy rate, 90%,
outperformed other methods. The proposed methodology proved
efficient by using a reduced number of attributes and did not
require human interaction for feature extraction (landmarks).",
conference-location = "Niter{\'o}i, RJ, Brazil",
conference-year = "17-20 Oct. 2017",
doi = "10.1109/SIBGRAPI.2017.32",
url = "http://dx.doi.org/10.1109/SIBGRAPI.2017.32",
language = "en",
ibi = "8JMKD3MGPAW/3PEUQJS",
url = "http://urlib.net/ibi/8JMKD3MGPAW/3PEUQJS",
targetfile = "sibgrapi-2017-cr.pdf",
urlaccessdate = "2024, Apr. 29"
}