I. Sreedevi, Rishi Pandey, N. Jayanthi, Geetanjali Bhola, S. Chaudhury
{"title":"碑文图像增强","authors":"I. Sreedevi, Rishi Pandey, N. Jayanthi, Geetanjali Bhola, S. Chaudhury","doi":"10.1109/NCC.2013.6488017","DOIUrl":null,"url":null,"abstract":"This paper addresses the problems encountered during digitization and preservation of inscriptions such as perspective distortion and minimal distinction between foreground and background. In general inscriptions neither possess standard size and shape nor colour difference between the foreground and background. Hence the existing methods like variance based extraction and Fast-ICA based analysis fail to extract text from these inscription images. Natural gradient Flexible ICA (NGFICA) is a suitable method for separating signals from a mixture of highly correlated signals, as it minimizes the dependency among the signals by considering the slope of the signal at each point. We propose an NGFICA based enhancement of inscription images. The proposed method improves word and character recognition accuracies of the OCR system by 65.3% (from 10.1% to 75.4%) and 54.3% (from 32.4% to 86.7%) respectively.","PeriodicalId":202526,"journal":{"name":"2013 National Conference on Communications (NCC)","volume":"177 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Enhancement of inscription images\",\"authors\":\"I. Sreedevi, Rishi Pandey, N. Jayanthi, Geetanjali Bhola, S. Chaudhury\",\"doi\":\"10.1109/NCC.2013.6488017\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper addresses the problems encountered during digitization and preservation of inscriptions such as perspective distortion and minimal distinction between foreground and background. In general inscriptions neither possess standard size and shape nor colour difference between the foreground and background. Hence the existing methods like variance based extraction and Fast-ICA based analysis fail to extract text from these inscription images. Natural gradient Flexible ICA (NGFICA) is a suitable method for separating signals from a mixture of highly correlated signals, as it minimizes the dependency among the signals by considering the slope of the signal at each point. We propose an NGFICA based enhancement of inscription images. The proposed method improves word and character recognition accuracies of the OCR system by 65.3% (from 10.1% to 75.4%) and 54.3% (from 32.4% to 86.7%) respectively.\",\"PeriodicalId\":202526,\"journal\":{\"name\":\"2013 National Conference on Communications (NCC)\",\"volume\":\"177 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-03-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 National Conference on Communications (NCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NCC.2013.6488017\",\"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 National Conference on Communications (NCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NCC.2013.6488017","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper addresses the problems encountered during digitization and preservation of inscriptions such as perspective distortion and minimal distinction between foreground and background. In general inscriptions neither possess standard size and shape nor colour difference between the foreground and background. Hence the existing methods like variance based extraction and Fast-ICA based analysis fail to extract text from these inscription images. Natural gradient Flexible ICA (NGFICA) is a suitable method for separating signals from a mixture of highly correlated signals, as it minimizes the dependency among the signals by considering the slope of the signal at each point. We propose an NGFICA based enhancement of inscription images. The proposed method improves word and character recognition accuracies of the OCR system by 65.3% (from 10.1% to 75.4%) and 54.3% (from 32.4% to 86.7%) respectively.