{"title":"Image in-painting techniques - A survey and analysis","authors":"S. Ravi, P. Pasupathi, S. Muthukumar, N. Krishnan","doi":"10.1109/INNOVATIONS.2013.6544390","DOIUrl":null,"url":null,"abstract":"Digital in-painting is relatively a young research area, yet a large variety of techniques were proposed by the researchers to correct the occlusion. Image in-painting aims to restore images with partly information loss and tries to make in-painting results as these missing parts in such a way that the reconstructed image looks natural. Many different types of image in-painting algorithms exist in the literature. However no recent study has been undertaken for a comparative evaluation of these algorithms to provide a comprehensive visualization. This paper compares different types of image in-painting algorithms. The algorithms are analyzed in both theoretical and experimental ways, which have made the suitability of these image in-painting algorithms over different kinds of applications in diversified areas.","PeriodicalId":438270,"journal":{"name":"2013 9th International Conference on Innovations in Information Technology (IIT)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 9th International Conference on Innovations in Information Technology (IIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INNOVATIONS.2013.6544390","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 16
Abstract
Digital in-painting is relatively a young research area, yet a large variety of techniques were proposed by the researchers to correct the occlusion. Image in-painting aims to restore images with partly information loss and tries to make in-painting results as these missing parts in such a way that the reconstructed image looks natural. Many different types of image in-painting algorithms exist in the literature. However no recent study has been undertaken for a comparative evaluation of these algorithms to provide a comprehensive visualization. This paper compares different types of image in-painting algorithms. The algorithms are analyzed in both theoretical and experimental ways, which have made the suitability of these image in-painting algorithms over different kinds of applications in diversified areas.