{"title":"Sensibility analysis of the Trace Transform on land coverage images","authors":"Ricardo Roman Brenes, F. Torres-Rojas, A. Ossa","doi":"10.1109/IWOBI.2015.7160149","DOIUrl":null,"url":null,"abstract":"Aerial or satellital images may be used to produce terrain coverage maps, which in time are a very useful and important tool for decision-making in several fields including biodiversity, telecommunications and natural disaster management. The Trace Transform method can be used to process these images. This method extracts features from the images by applying a series of functionals to produce a numeric representation that will be used for classification later on. This model depends on several factors in order to have an efficient operation, among them, the frequency parameters of the traces, classifier type and land coverage. Experimentation on feature extraction time and precision rate revealed that the frequency parameters, specially Δτ, and the classifier type can affect both of them.","PeriodicalId":373170,"journal":{"name":"2015 4th International Work Conference on Bioinspired Intelligence (IWOBI)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 4th International Work Conference on Bioinspired Intelligence (IWOBI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWOBI.2015.7160149","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Aerial or satellital images may be used to produce terrain coverage maps, which in time are a very useful and important tool for decision-making in several fields including biodiversity, telecommunications and natural disaster management. The Trace Transform method can be used to process these images. This method extracts features from the images by applying a series of functionals to produce a numeric representation that will be used for classification later on. This model depends on several factors in order to have an efficient operation, among them, the frequency parameters of the traces, classifier type and land coverage. Experimentation on feature extraction time and precision rate revealed that the frequency parameters, specially Δτ, and the classifier type can affect both of them.