{"title":"基于两种互补算法组合的退化文档图像二值化","authors":"M. Valizadeh, M. Komeili, N. Armanfard, E. Kabir","doi":"10.1109/ACTEA.2009.5227898","DOIUrl":null,"url":null,"abstract":"In this paper we combine two binarization algorithms that are complementary to each other. The main idea is to select the better algorithm in each part of document image. There are algorithms that properly distinguish the text from the background in the regions close to the text, but get wrong in the regions far from the text and introduce some part of background as text. We propose a new binarization algorithm that effectively eliminates background and reliably extracts some parts of each character. Then according to the distance of each pixel form the text, the appropriate algorithm is selected to binarize that pixel. Proposed method is applicable for various types of degraded document images. After extensive experiment, the proposed binarization algorithm demonstrate superior performance against four well-know binarization algorithms on a set of degraded document images captured with camera.","PeriodicalId":308909,"journal":{"name":"2009 International Conference on Advances in Computational Tools for Engineering Applications","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"Degraded document image binarization based on combination of two complementary algorithms\",\"authors\":\"M. Valizadeh, M. Komeili, N. Armanfard, E. Kabir\",\"doi\":\"10.1109/ACTEA.2009.5227898\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we combine two binarization algorithms that are complementary to each other. The main idea is to select the better algorithm in each part of document image. There are algorithms that properly distinguish the text from the background in the regions close to the text, but get wrong in the regions far from the text and introduce some part of background as text. We propose a new binarization algorithm that effectively eliminates background and reliably extracts some parts of each character. Then according to the distance of each pixel form the text, the appropriate algorithm is selected to binarize that pixel. Proposed method is applicable for various types of degraded document images. After extensive experiment, the proposed binarization algorithm demonstrate superior performance against four well-know binarization algorithms on a set of degraded document images captured with camera.\",\"PeriodicalId\":308909,\"journal\":{\"name\":\"2009 International Conference on Advances in Computational Tools for Engineering Applications\",\"volume\":\"53 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-07-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Conference on Advances in Computational Tools for Engineering Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ACTEA.2009.5227898\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference on Advances in Computational Tools for Engineering Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACTEA.2009.5227898","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Degraded document image binarization based on combination of two complementary algorithms
In this paper we combine two binarization algorithms that are complementary to each other. The main idea is to select the better algorithm in each part of document image. There are algorithms that properly distinguish the text from the background in the regions close to the text, but get wrong in the regions far from the text and introduce some part of background as text. We propose a new binarization algorithm that effectively eliminates background and reliably extracts some parts of each character. Then according to the distance of each pixel form the text, the appropriate algorithm is selected to binarize that pixel. Proposed method is applicable for various types of degraded document images. After extensive experiment, the proposed binarization algorithm demonstrate superior performance against four well-know binarization algorithms on a set of degraded document images captured with camera.