Automatic counting of Aedes Aegypti eggs deposited in ovitrap by algorithm of Digital Image Processing and Artificial Neural Network

Author

Elpídio, F. G G ; Costa, L.F.R. ; Andrade, M.M. ; Costa, E.A., Jr. ; Brasil, L.M. ; Rodrigues, M.A.B.

Author_Institution

Fac. Gama, Univ. de Brasilia, Gama, Brazil

fYear

2011

fDate

March 28 2011-April 1 2011

Firstpage

138

Lastpage

139

Abstract

According to World Health Organization, Dengue is identified as one of the main pandemic viral disease in tropical and semi-tropical countries in the world. A lot of researches have divulged that the use of ovitraps has itself shown a simple and inexpensive alternative for monitoring and controlling Dengue vector, Aedes Aegypti, but generally the process of counting Dengue mosquito eggs in ovitraps is performed manually. This paper describes a proposal for automatic counting of Aedes Aegypti eggs deposited in ovitraps by Digital Image Processing techniques associated to an Artificial Neural Network.

Keywords

biological techniques; biology computing; diseases; image processing; neural nets; zoology; Aedes Aegypti egg automatic counting; artificial neural network; dengue; digital image processing; ovitrap; pandemic viral disease; Artificial neural networks; Manuals; Medical services; Pixel; Process control; RNA; Artificial Neural Network; Dengue; Digital Image Processing; Ovitraps;

fLanguage

English

Publisher

ieee

Conference_Titel

Health Care Exchanges (PAHCE), 2011 Pan American

Conference_Location

Rio de Janeiro

Print_ISBN

978-1-61284-915-7

Type

conf

DOI

10.1109/PAHCE.2011.5871865

Filename

5871865