{"title":"文档图像的分割和文本提取:综述","authors":"Gururaj Mukarambi, Hema Gaikwadl, B. V. Dhandra","doi":"10.1109/i-PACT44901.2019.8960097","DOIUrl":null,"url":null,"abstract":"Segmentation and text extraction from complex document image helps in analyzing, storing, retrieving and auto indexing of required information. In this paper, we considered 23 existing methods of segmentation and text extraction for complex document images. After review of the existing methods, we found that connected component method [1],[2],[5],[8],[10],[13] are more suitable for segmentation of text and non-text from document and also LSTM &RNN found that potential methods for extraction of text from complex document[15].","PeriodicalId":214890,"journal":{"name":"2019 Innovations in Power and Advanced Computing Technologies (i-PACT)","volume":"126 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Segmentation and Text extraction from Document Images: Survey\",\"authors\":\"Gururaj Mukarambi, Hema Gaikwadl, B. V. Dhandra\",\"doi\":\"10.1109/i-PACT44901.2019.8960097\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Segmentation and text extraction from complex document image helps in analyzing, storing, retrieving and auto indexing of required information. In this paper, we considered 23 existing methods of segmentation and text extraction for complex document images. After review of the existing methods, we found that connected component method [1],[2],[5],[8],[10],[13] are more suitable for segmentation of text and non-text from document and also LSTM &RNN found that potential methods for extraction of text from complex document[15].\",\"PeriodicalId\":214890,\"journal\":{\"name\":\"2019 Innovations in Power and Advanced Computing Technologies (i-PACT)\",\"volume\":\"126 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 Innovations in Power and Advanced Computing Technologies (i-PACT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/i-PACT44901.2019.8960097\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Innovations in Power and Advanced Computing Technologies (i-PACT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/i-PACT44901.2019.8960097","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Segmentation and Text extraction from Document Images: Survey
Segmentation and text extraction from complex document image helps in analyzing, storing, retrieving and auto indexing of required information. In this paper, we considered 23 existing methods of segmentation and text extraction for complex document images. After review of the existing methods, we found that connected component method [1],[2],[5],[8],[10],[13] are more suitable for segmentation of text and non-text from document and also LSTM &RNN found that potential methods for extraction of text from complex document[15].