title: Image segmentation of ovitraps for automatic counting of Aedes Aegypti eggs.
abstract: The Aedes Aegypti mosquito is the vector of the most difficult public health problems in tropical and semi-tropical world: the epidemic proliferation of dengue, a viral disease that can cause human beings death specially in its most dangerous form, dengue haemorrhagic fever. One of the most useful methods for mosquito detection and surveillance is the ovitraps: special traps to collect eggs of the mosquito. It is very important to count the number of Aedes Aegypti eggs present in ovitraps. This counting is usually performed in a manual, visual and non-automatic form. This work approaches the development of automatic methods to count the number of eggs in ovitraps images using image processing, particularly color segmentation and mathematical morphology-based non-linear filters.
authors.affiliation: Department of Computing and Systems, University of Pernambuco, Recife, Brazil. carlos@dsc.upe.br
authors.forename: Carlos A B
authors.initials: CA
authors.lastname: Mello
authors.forename: Wellington P
authors.initials: WP
authors.lastname: dos Santos
authors.forename: Marco A B
authors.initials: MA
authors.lastname: Rodrigues
authors.forename: Ana Lúcia B
authors.initials: AL
authors.lastname: Candeias
authors.forename: Cristine M G
authors.initials: CM
authors.lastname: Gusmão
mesh_terms: D000330:Aedes / Q000502:physiology*; D000465:Algorithms; D000818:Animals; D001331:Automation; D001330:Electronic Data Processing; D007091:Image Processing, Computer-Assisted; D009032:Mosquito Control / Q000379:methods*; D010058:Oviposition; D010063:Ovum; D010781:Photography / Q000379:methods; D011157:Population Dynamics; D011159:Population Surveillance; D015203:Reproducibility of Results; D012984:Software