A. Martynenko, A. Tevyashev, N. Kulishova, B. Moroz
{"title":"System analysis of the problem of establishing the authenticity and authority of painting works","authors":"A. Martynenko, A. Tevyashev, N. Kulishova, B. Moroz","doi":"10.20535/srit.2308-8893.2022.1.04","DOIUrl":null,"url":null,"abstract":"Cultural values have long been the objects of crimes, among which the export from the state stands out. Falsification hides artworks from customs control and its detection requires a long examination using a variety of methods of analysis. This article discusses the task of verifying painting’s authenticity during customs inspection. A two-stage procedure is proposed, which includes a quick check based on the analysis of painting’s images and a longer museum expertize. To implement the image analysis, it is proposed to use an intelligent decision-making system, which is based on a classifier that implements the k-nearest neighbors algorithm. A set of features to describe painting’s properties is formed, metrics for calculating the similarity measure on objects in the course of classification is proposed. To train an algorithm, a dataset is proposed, which includes paintings by world and European artists, as well as Ukrainian painters from different centuries.","PeriodicalId":330635,"journal":{"name":"System research and information technologies","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"System research and information technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.20535/srit.2308-8893.2022.1.04","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Cultural values have long been the objects of crimes, among which the export from the state stands out. Falsification hides artworks from customs control and its detection requires a long examination using a variety of methods of analysis. This article discusses the task of verifying painting’s authenticity during customs inspection. A two-stage procedure is proposed, which includes a quick check based on the analysis of painting’s images and a longer museum expertize. To implement the image analysis, it is proposed to use an intelligent decision-making system, which is based on a classifier that implements the k-nearest neighbors algorithm. A set of features to describe painting’s properties is formed, metrics for calculating the similarity measure on objects in the course of classification is proposed. To train an algorithm, a dataset is proposed, which includes paintings by world and European artists, as well as Ukrainian painters from different centuries.