Rohan Hatekar, Pratik Gawli, Rakshak R Kamath, A. Deshpande
{"title":"Detection of Mosquito using Digital Image Processing","authors":"Rohan Hatekar, Pratik Gawli, Rakshak R Kamath, A. Deshpande","doi":"10.1109/CCICT53244.2021.00050","DOIUrl":null,"url":null,"abstract":"Mosquito borne diseases are a worldwide problem and to recognize these diseases, we need to find a long lasting solution. We need an alternative to keep these insects away from humans in order to cut down the many lives it takes away. In this project, the system has developed a method to identify mosquitoes using digital image processing techniques and neural networks to classify them. The system also proposes to develop a system which will maintain a record of the collected data which can be used for different studies or eliminate them. The developed system distinguishes these mosquitoes by analyzing their morphological characteristics and use color-based analysis for distinguish these species. The challenges in designing such an automated system is the algorithm to be chosen for detection, which features to be chosen and choosing the hardware for real-time implementation.","PeriodicalId":213095,"journal":{"name":"2021 Fourth International Conference on Computational Intelligence and Communication Technologies (CCICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 Fourth International Conference on Computational Intelligence and Communication Technologies (CCICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCICT53244.2021.00050","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Mosquito borne diseases are a worldwide problem and to recognize these diseases, we need to find a long lasting solution. We need an alternative to keep these insects away from humans in order to cut down the many lives it takes away. In this project, the system has developed a method to identify mosquitoes using digital image processing techniques and neural networks to classify them. The system also proposes to develop a system which will maintain a record of the collected data which can be used for different studies or eliminate them. The developed system distinguishes these mosquitoes by analyzing their morphological characteristics and use color-based analysis for distinguish these species. The challenges in designing such an automated system is the algorithm to be chosen for detection, which features to be chosen and choosing the hardware for real-time implementation.