{"title":"基于纹理特征的古代退化文档图像二值化","authors":"A. Sehad, Y. Chibani, M. Cheriet, Yacine Yaddaden","doi":"10.1109/ISPA.2013.6703737","DOIUrl":null,"url":null,"abstract":"In this paper, we present a promising method for binarization of historical and degraded document images, based on texture features. The proposed method is an adaptive threshold-based. This latter is computed by using a descriptor based on a co-occurrence matrix. The proposed method is tested objectively, using DIBCO dataset degraded documents and subjectively, using a set of ancient degraded documents provided by a national library. The results are satisfactory and promising, and present an improvement to classical methods.","PeriodicalId":425029,"journal":{"name":"2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":"{\"title\":\"Ancient degraded document image binarization based on texture features\",\"authors\":\"A. Sehad, Y. Chibani, M. Cheriet, Yacine Yaddaden\",\"doi\":\"10.1109/ISPA.2013.6703737\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we present a promising method for binarization of historical and degraded document images, based on texture features. The proposed method is an adaptive threshold-based. This latter is computed by using a descriptor based on a co-occurrence matrix. The proposed method is tested objectively, using DIBCO dataset degraded documents and subjectively, using a set of ancient degraded documents provided by a national library. The results are satisfactory and promising, and present an improvement to classical methods.\",\"PeriodicalId\":425029,\"journal\":{\"name\":\"2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA)\",\"volume\":\"42 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"22\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISPA.2013.6703737\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPA.2013.6703737","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Ancient degraded document image binarization based on texture features
In this paper, we present a promising method for binarization of historical and degraded document images, based on texture features. The proposed method is an adaptive threshold-based. This latter is computed by using a descriptor based on a co-occurrence matrix. The proposed method is tested objectively, using DIBCO dataset degraded documents and subjectively, using a set of ancient degraded documents provided by a national library. The results are satisfactory and promising, and present an improvement to classical methods.