Document Type
Article
Publication Date
May 2024
Patent Number
11989936
CPC
G06V 10/56 , G06V 10/44
Abstract
Identifying insect species integrates image processing, feature selection, unsupervised clustering, and a support vector machine (SVM) learning algorithm for classification. Results with a total of 101 mosquito specimens spread across nine different vector carrying species demonstrate high accuracy in species identification. When implemented as a smart-phone application, the latency and energy consumption were minimal. The currently manual process of species identification and recording can be sped up, while also minimizing the ensuing cognitive workload of personnel. Citizens at large can use the system in their own homes for self-awareness and share insect identification data with public health agencies.
Application Number
17/901494
Recommended Citation
Chellappan, Sriram; Bharti, Pratool; Minakshi, Mona; McClinton, Willie; and Mirzakhalov, Jamshidbek, "Leveraging smart-phone cameras and image processing techniques to classify mosquito genus and species" (2024). USF Patents. 1422.
https://digitalcommons.usf.edu/usf_patents/1422
Assignees
University of South Florida
Filing Date
09/01/2022
