A new algorithm for segmenting and counting Aedes aegypti eggs in ovitraps
| Autor: | S. C. S. Machado, Marco Aurélio Benedetti Rodrigues, G. Gusmao |
|---|---|
| Rok vydání: | 2009 |
| Předmět: |
Mosquito Control
Population Cell Count Aedes aegypti Biology Public healthcare Dengue fever Dengue Aedes Statistics medicine Image Processing Computer-Assisted Animals Cluster Analysis Computer vision education Ovum education.field_of_study business.industry fungi medicine.disease biology.organism_classification Geographic Information Systems Artificial intelligence business Algorithms |
| Zdroj: | Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference. 2009 |
| ISSN: | 2375-7477 |
| Popis: | Dengue fever has become a major international public health concern in recent decades. As dengue fever not have available vaccine or specific treatment, the only known form to prevent the illness is by applying strategies to control its vector, the Aedes aegypti mosquito. Ovitraps, special traps to collect mosquito eggs, are used to detect Aedes aegypti presence and to approximate the gauge of the adult mosquitoes population in the environment by counting the number of eggs laid in an trap. This counting is usually performed in a manual, visual and non-automatic form. This work proposes a new automatic method to automatically count the number of eggs in digital images of ovitraps based on image processing techniques (color systems exploration) and k-Means clustering algorithm. The proposed method performs an improvement on the results when compared with previous studies. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|