2016 12th IAPR Workshop on Document Analysis Systems (DAS)最新文献_第5页

Automatic Selection of Parameters for Document Image Enhancement Using Image Quality Assessment 使用图像质量评估的文档图像增强参数的自动选择

2016 12th IAPR Workshop on Document Analysis Systems (DAS) Pub Date : 2016-04-11 DOI: 10.1109/DAS.2016.53

Ritu Garg, S. Chaudhury

引用次数: 6

Creating Ground Truth for Historical Manuscripts with Document Graphs and Scribbling Interaction 用文献图表和涂鸦互动创造历史手稿的基础真相

2016 12th IAPR Workshop on Document Analysis Systems (DAS) Pub Date : 2016-04-11 DOI: 10.1109/DAS.2016.29

A. Garz, Mathias Seuret, Fotini Simistira, Andreas Fischer, R. Ingold

引用次数: 24

High Performance OCR for Camera-Captured Blurred Documents with LSTM Networks 用LSTM网络对相机捕获的模糊文件进行高性能OCR

2016 12th IAPR Workshop on Document Analysis Systems (DAS) Pub Date : 2016-04-11 DOI: 10.1109/DAS.2016.69

Fallak Asad, A. Ul-Hasan, F. Shafait, A. Dengel

{"title":"High Performance OCR for Camera-Captured Blurred Documents with LSTM Networks","authors":"Fallak Asad, A. Ul-Hasan, F. Shafait, A. Dengel","doi":"10.1109/DAS.2016.69","DOIUrl":"https://doi.org/10.1109/DAS.2016.69","url":null,"abstract":"Documents are routinely captured by digital cameras in today's age owing to the availability of high quality cameras in smart phones. However, recognition of camera-captured documents is substantially more challenging as compared to traditional flat bed scanned documents due to the distortions introduced by the cameras. One of the major performancelimiting artifacts is the motion and out-of-focus blur that is often induced in the document during the capturing process. Existing approaches try to detect presence of blur in the document to inform the user for re-capturing the image. This paper reports, for the first time, an Optical Character Recognition (OCR) system that can directly recognize blurred documents on which the stateof-the-art OCR systems are unable to provide usable results. Our presented system is based on the Long Short-Term Memory (LSTM) networks and has shown promising character recognition results on both the motion-blurred and out-of-focus blurred images. One important feature of this work is that the LSTM networks have been applied directly to the gray-scale document images to avoid error-prone binarization of blurred documents. Experiments are conducted on publicly available SmartDoc-QA dataset that contains a wide variety of image blur degradations. Our presented system achieves 12.3% character error rate on the test documents, which is an over three-fold reduction in the error rate (38.9%) of the best-performing contemporary OCR system (ABBYY Fine Reader) on the same data.","PeriodicalId":197359,"journal":{"name":"2016 12th IAPR Workshop on Document Analysis Systems (DAS)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125716320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 14

Document Image Quality Assessment Based on Texture Similarity Index 基于纹理相似度指数的文档图像质量评价

2016 12th IAPR Workshop on Document Analysis Systems (DAS) Pub Date : 2016-04-11 DOI: 10.1109/DAS.2016.33

Alireza Alaei, Donatello Conte, M. Blumenstein, R. Raveaux

引用次数: 11

A Compliant Document Image Classification System Based on One-Class Classifier 基于单类分类器的兼容文档图像分类系统

2016 12th IAPR Workshop on Document Analysis Systems (DAS) Pub Date : 2016-04-11 DOI: 10.1109/DAS.2016.55

Nicolas Sidère, Jean-Yves Ramel, Sabine Barrat, V. P. d'Andecy, S. Kebairi

引用次数: 0

Error Detection in Indic OCRs 索引ocr中的错误检测

2016 12th IAPR Workshop on Document Analysis Systems (DAS) Pub Date : 2016-04-11 DOI: 10.1109/DAS.2016.31

V. Vinitha, C. V. Jawahar

引用次数: 10

An Interactive Transcription System of Census Records Using Word-Spotting Based Information Transfer 基于字词信息传递的交互式人口普查记录转录系统

2016 12th IAPR Workshop on Document Analysis Systems (DAS) Pub Date : 2016-04-11 DOI: 10.1109/DAS.2016.47

J. M. Romeu, A. Fornés, J. Lladós

{"title":"An Interactive Transcription System of Census Records Using Word-Spotting Based Information Transfer","authors":"J. M. Romeu, A. Fornés, J. Lladós","doi":"10.1109/DAS.2016.47","DOIUrl":"https://doi.org/10.1109/DAS.2016.47","url":null,"abstract":"This paper presents a system to assist in the transcription of historical handwritten census records in a crowdsourcing platform. Census records have a tabular structured layout. They consist in a sequence of rows with information of homes ordered by street address. For each household snippet in the page, the list of family members is reported. The censuses are recorded in intervals of a few years and the information of individuals in each household is quite stable from a point in time to the next one. This redundancy is used to assist the transcriber, so the redundant information is transferred from the census already transcribed to the next one. Household records are aligned from one year to the next one using the knowledge of the ordering by street address. Given an already transcribed census, a query by string word spotting is applied. Thus, names from the census in time t are used as queries in the corresponding home record in time t+1. Since the search is constrained, the obtained precision-recall values are very high, with an important reduction in the transcription time. The proposed system has been tested in a real citizen-science experience where non expert users transcribe the census data of their home town.","PeriodicalId":197359,"journal":{"name":"2016 12th IAPR Workshop on Document Analysis Systems (DAS)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129831871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Effective Candidate Component Extraction for Text Localization in Born-Digital Images by Combining Text Contours and Stroke Interior Regions 基于文本轮廓和笔画内区域相结合的数字图像文本定位有效候选成分提取

2016 12th IAPR Workshop on Document Analysis Systems (DAS) Pub Date : 2016-04-11 DOI: 10.1109/DAS.2016.30

Kai Chen, Fei Yin, Cheng-Lin Liu

{"title":"Effective Candidate Component Extraction for Text Localization in Born-Digital Images by Combining Text Contours and Stroke Interior Regions","authors":"Kai Chen, Fei Yin, Cheng-Lin Liu","doi":"10.1109/DAS.2016.30","DOIUrl":"https://doi.org/10.1109/DAS.2016.30","url":null,"abstract":"Extracting candidate text connected components (CCs) is critical for CC-based text localization. Based on the observation that text strokes in born-digital images mostly have complete contours and the text pixels have high contrast with the adjacent non-text pixels, we propose a method to extract candidate text CCs by combining text contours and stroke interior regions. After segmenting the image into non-smooth and smooth regions based on local contrast, text contour pixels in non-smooth regions are detached from adjacent non-text pixels by local binarization. Then, obvious non-text contours can be removed according to the spatial relationship of text and non-text contours. While smooth regions include stroke interior regions and non-text smooth regions, some non-text smooth regions can be easily removed because they are not surrounded by candidate text contours. At last, candidate text contours and stroke interior regions are combined to generate candidate text CCs. The CCs undergo CC filtering, text line grouping and line classification to give the text localization result. Experimental results on the born-digital dataset of ICDAR2013 robust reading competition demonstrate the efficiency and superiority of the proposed method.","PeriodicalId":197359,"journal":{"name":"2016 12th IAPR Workshop on Document Analysis Systems (DAS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127488207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Quality Prediction System for Large-Scale Digitisation Workflows 面向大规模数字化工作流的质量预测系统

2016 12th IAPR Workshop on Document Analysis Systems (DAS) Pub Date : 2016-04-11 DOI: 10.1109/DAS.2016.82

C. Clausner, S. Pletschacher, A. Antonacopoulos

引用次数: 8

Semi-automatic Text and Graphics Extraction of Manga Using Eye Tracking Information 基于眼动追踪信息的漫画半自动文本和图形提取

2016 12th IAPR Workshop on Document Analysis Systems (DAS) Pub Date : 2016-04-11 DOI: 10.1109/DAS.2016.72

Christophe Rigaud, Thanh Nam Le, J. Burie, J. Ogier, Shoya Ishimaru, M. Iwata, K. Kise

引用次数: 10