• E.Ambica

This paper uses a classification algorithm for the recognition of Aedes mosquito using the image processing techniques. Aedes mosquitoes are the carrier of dengue virus. The dengue fever is a fatal disease which does not have vaccine or treatment. Thus eliminating the Aedes population is the only remedy available to reduce the risk of dengue fever. Image processing techniques help in recognizing the Aedes mosquitoes in the image that is taken from the mosquito-prone area. The recognition of Aedes mosquito is done through a trained classifier using the image features. The image feature is the white patch in the body and legs of Aedes mosquito which is extracted by processing the RGB channel of the image. The classifier is trained based on the extracted image features. The trained classifier categorizes the mosquito image into ‘Aedes’ and ‘Non-Aedes’ classes. In the real-world environment, the number of classes of mosquito increases dynamically, so there is a need for a classifier to adapt to the growing categories. To adapt to the increasing number of classes, a hybrid incremental algorithm Nearest Class Mean Forests (NCMF) method is used, which is a variant of random forest method. The system is trained and tested using the mosquito images.

Aedes mosquito, threshold, nearest class mean classifier, random forest

"Recognition and classification of Aedes aegypti using image processing techniques ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 5, page no.664-667, May-2018, Available :http://www.jetir.org/papers/JETIR1805530.pdf

"Recognition and classification of Aedes aegypti using image processing techniques ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 5, page no. pp664-667, May-2018, Available at : http://www.jetir.org/papers/JETIR1805530.pdf