Verónica Romero, A. Toselli, Joan Andreu Sánchez, E. Vidal
{"title":"Handwriting Transcription and Keyword Spotting in Historical Daily Records Documents","authors":"Verónica Romero, A. Toselli, Joan Andreu Sánchez, E. Vidal","doi":"10.1109/DAS.2016.70","DOIUrl":"https://doi.org/10.1109/DAS.2016.70","url":null,"abstract":"Historical records of daily activities provide an intriguing look into the historic life. These documents have interesting information, useful for demography studies and genealogical research. However, automatic processing of historical documents, has mostly been focused on single works of literature and less on daily records, which tend to have a distinct layout, structure, and vocabulary. This paper presents a study about the capability of state-of-the-art handwritten text recognition and key word spotting systems, when applied to this kind of documents. A relatively small set of handwritten birth records registered in Wien in the 16th century is used in the experiments. A word accuracy of about 70% and an AP of 0.74 are achieved for plain image transcription and key word spotting respectively. Taking into account the many difficulties exhibited by these handwritten documents, these preliminary results are quite encouraging.","PeriodicalId":197359,"journal":{"name":"2016 12th IAPR Workshop on Document Analysis Systems (DAS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116445239","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}
Dimosthenis Karatzas, V. P. d'Andecy, Marçal Rusiñol, A. Chica, Pere-Pau Vázquez
{"title":"Human-Document Interaction Systems -- A New Frontier for Document Image Analysis","authors":"Dimosthenis Karatzas, V. P. d'Andecy, Marçal Rusiñol, A. Chica, Pere-Pau Vázquez","doi":"10.1109/DAS.2016.65","DOIUrl":"https://doi.org/10.1109/DAS.2016.65","url":null,"abstract":"All indications show that paper documents will not cede in favour of their digital counterparts, but will instead be used increasingly in conjunction with digital information. An open challenge is how to seamlessly link the physical with the digital -- how to continue taking advantage of the important affordances of paper, without missing out on digital functionality. This paper presents the authors' experience with developing systems for Human-Document Interaction based on augmented document interfaces and examines new challenges and opportunities arising for the document image analysis field in this area. The system presented combines state of the art camera-based document image analysis techniques with a range of complementary technologies to offer fluid Human-Document Interaction. Both fixed and nomadic setups are discussed that have gone through user testing in real-life environments, and use cases are presented that span the spectrum from business to educational applications.","PeriodicalId":197359,"journal":{"name":"2016 12th IAPR Workshop on Document Analysis Systems (DAS)","volume":"657 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116486078","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}
{"title":"Modified X-Y Cut for Re-Ordering Strokes of Online Handwritten Mathematical Expressions","authors":"A. D. Le, Hai Dai Nguyen, M. Nakagawa","doi":"10.1109/DAS.2016.19","DOIUrl":"https://doi.org/10.1109/DAS.2016.19","url":null,"abstract":"This paper proposes a modified X-Y cut method for reordering strokes of online handwritten mathematical expression (ME) in order to make stroke order free recognition. To deal with overlapping, which causes problems in the X-Y cut method, we determine vertically ordered strokes by detecting vertical symbols and its upper/lower MEs. An upper ME and a lower ME are treated as MEs which are reordered recursively. Unordered strokes on the left side of a vertical symbol are reordered as horizontally ordered strokes. The remaining strokes are reordered recursively. The horizontally ordered strokes are reordered from left to right and the vertically ordered strokes are reordered from top to bottom. The results of evaluations of the reordering method on the CROHME 2014 database show that our ME recognition system incorporating this method outperforms all other systems that use only CROHME 2014 for training while the processing time is kept to a practical level.","PeriodicalId":197359,"journal":{"name":"2016 12th IAPR Workshop on Document Analysis Systems (DAS)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134477679","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}
{"title":"A Fine-Grained Approach to Scene Text Script Identification","authors":"L. G. I. Bigorda, Dimosthenis Karatzas","doi":"10.1109/DAS.2016.64","DOIUrl":"https://doi.org/10.1109/DAS.2016.64","url":null,"abstract":"This paper focuses on the problem of script identification in unconstrained scenarios. Script identification is an important prerequisite to recognition, and an indispensable condition for automatic text understanding systems designed for multi-language environments. Although widely studied for document images and handwritten documents, it remains an almost unexplored territory for scene text images. We detail a novel method for script identification in natural images that combines convolutional features and the Naive-Bayes Nearest Neighbor classifier. The proposed framework efficiently exploits the discriminative power of small stroke-parts, in a fine-grained classification framework. In addition, we propose a new public benchmark dataset for the evaluation of joint text detection and script identification in natural scenes. Experiments done in this new dataset demonstrate that the proposed method yields state of the art results, while it generalizes well to different datasets and variable number of scripts. The evidence provided shows that multi-lingual scene text recognition in the wild is a viable proposition. Source code of the proposed method is made available online.","PeriodicalId":197359,"journal":{"name":"2016 12th IAPR Workshop on Document Analysis Systems (DAS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133910251","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}
Anguelos Nicolaou, Andrew D. Bagdanov, L. G. I. Bigorda, Dimosthenis Karatzas
{"title":"Visual Script and Language Identification","authors":"Anguelos Nicolaou, Andrew D. Bagdanov, L. G. I. Bigorda, Dimosthenis Karatzas","doi":"10.1109/DAS.2016.63","DOIUrl":"https://doi.org/10.1109/DAS.2016.63","url":null,"abstract":"In this paper we introduce a script identification method based on hand-crafted texture features and an artificial neural network. The proposed pipeline achieves near state-of-the-art performance for script identification of video-text and state-of-the-art performance on visual language identification of handwritten text. More than using the deep network as a classifier, the use of its intermediary activations as a learned metric demonstrates remarkable results and allows the use of discriminative models on unknown classes. Comparative experiments in video-text and text in the wild datasets provide insights on the internals of the proposed deep network.","PeriodicalId":197359,"journal":{"name":"2016 12th IAPR Workshop on Document Analysis Systems (DAS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129535737","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}