I. Pavlidis, Douglas P. Perrin, N. Papanikolopoulos, W. Au, S. Sawtelle
{"title":"A ground truth tool for Synthetic Aperture Radar (SAR) imagery","authors":"I. Pavlidis, Douglas P. Perrin, N. Papanikolopoulos, W. Au, S. Sawtelle","doi":"10.1109/CVBVS.1999.781097","DOIUrl":null,"url":null,"abstract":"The performance of computer vision algorithms has made great strides and it is good enough to be useful in a number of civilian and military applications. Algorithm advancement in Automatic Target Recognition (ATR) in particular; has reached a critical point. State-of-the-art ATRs are capable of delivering robust performance for certain operational scenarios. As Computer Vision technology matures and algorithms enter the civilian and military marketplace as products, the lack of a formal testing theory and tools become obvious. In this paper we present the design and implementation of a Ground Truth Tool (GTT) for Synthetic Aperture Radar (SAR) imagery. The tool serves as part of an evaluation system for SAR ATRs. It features a semi-automatic method for delineating image objects that draws upon the theory of deformable models. In comparison with other deformable model implementations, our version is stable and is supported by an extensive Graphical User Interface (GUI). Preliminary experimental tests show that the system can substantially increase the productivity and accuracy of the image analyst (IA).","PeriodicalId":394469,"journal":{"name":"Proceedings IEEE Workshop on Computer Vision Beyond the Visible Spectrum: Methods and Applications (CVBVS'99)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings IEEE Workshop on Computer Vision Beyond the Visible Spectrum: Methods and Applications (CVBVS'99)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CVBVS.1999.781097","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
The performance of computer vision algorithms has made great strides and it is good enough to be useful in a number of civilian and military applications. Algorithm advancement in Automatic Target Recognition (ATR) in particular; has reached a critical point. State-of-the-art ATRs are capable of delivering robust performance for certain operational scenarios. As Computer Vision technology matures and algorithms enter the civilian and military marketplace as products, the lack of a formal testing theory and tools become obvious. In this paper we present the design and implementation of a Ground Truth Tool (GTT) for Synthetic Aperture Radar (SAR) imagery. The tool serves as part of an evaluation system for SAR ATRs. It features a semi-automatic method for delineating image objects that draws upon the theory of deformable models. In comparison with other deformable model implementations, our version is stable and is supported by an extensive Graphical User Interface (GUI). Preliminary experimental tests show that the system can substantially increase the productivity and accuracy of the image analyst (IA).