{"title":"A neural re-ranking method for searching ancient Arabic documents on the Web","authors":"T. Sari, Chaouki Chemam","doi":"10.1109/ISIICT.2011.6149609","DOIUrl":null,"url":null,"abstract":"Web users want a quick and accurate access to images. The method currently used by search engines is the analysis of text surrounding an image which usually causes errors. Since there is a huge gap between the content of the image and the textual description associated. Hence, realizing a search engine for images in the web considering their contents became therefore mandatory. In this paper, we propose a method for collecting images of old Arabic documents from the Web. This work focuses mainly on content based image retrieval by texture feature using a neural network for classification and trying to integrate the user in the search loop. The system begins with the formulation of a query text, which is expanded and sent to a conventional search engine. Then, the obtained results are filtered by a neural network and finally displayed to the user for agreement. The experiments with various query texts shown good performances and hundreds of old Arabic documents were collected.","PeriodicalId":266498,"journal":{"name":"International Symposium on Innovations in Information and Communications Technology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2011-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Symposium on Innovations in Information and Communications Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISIICT.2011.6149609","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
Web users want a quick and accurate access to images. The method currently used by search engines is the analysis of text surrounding an image which usually causes errors. Since there is a huge gap between the content of the image and the textual description associated. Hence, realizing a search engine for images in the web considering their contents became therefore mandatory. In this paper, we propose a method for collecting images of old Arabic documents from the Web. This work focuses mainly on content based image retrieval by texture feature using a neural network for classification and trying to integrate the user in the search loop. The system begins with the formulation of a query text, which is expanded and sent to a conventional search engine. Then, the obtained results are filtered by a neural network and finally displayed to the user for agreement. The experiments with various query texts shown good performances and hundreds of old Arabic documents were collected.